WO2020222408A1 - Procédé d'amélioration de trajet de point de cheminement en temps réel, support d'enregistrement dans lequel est stocké un programme de mise en œuvre du procédé, et programme informatique stocké dans un support pour sa mise en œuvre - Google Patents

Procédé d'amélioration de trajet de point de cheminement en temps réel, support d'enregistrement dans lequel est stocké un programme de mise en œuvre du procédé, et programme informatique stocké dans un support pour sa mise en œuvre Download PDF

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Publication number
WO2020222408A1
WO2020222408A1 PCT/KR2020/002360 KR2020002360W WO2020222408A1 WO 2020222408 A1 WO2020222408 A1 WO 2020222408A1 KR 2020002360 W KR2020002360 W KR 2020002360W WO 2020222408 A1 WO2020222408 A1 WO 2020222408A1
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WIPO (PCT)
Prior art keywords
waypoint
path
local
route
time
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PCT/KR2020/002360
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English (en)
Korean (ko)
Inventor
김태형
천홍석
이재훈
변용진
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주식회사 트위니
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1674—Programme controls characterised by safety, monitoring, diagnostic
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
    • B25J9/1697—Vision controlled systems

Definitions

  • the present invention relates to a real-time waypoint path improvement method, a recording medium in which a program for implementing the same is stored, and a computer program stored in the medium to implement the same, and more particularly, to a waypoint in the direction of the robot outside the sensor sensing area of the robot.
  • a target waypoint Is determined as a target waypoint, and a method for improving a real-time waypoint route that enables autonomous driving by finding a more challenging route for the robot to be more challenging, a recording medium in which a program for implementing this is stored, and a computer program stored in the medium to implement the same.
  • Autonomous robots refer to robots that search their surroundings and detect obstacles and use wheels or legs to find the optimal route to their destination.
  • Path planning or obstacle avoidance is an important element technology in autonomous driving of mobile robots.
  • the robot creates and moves to the destination, but must reach the destination without colliding with surrounding obstacles.
  • a good path means the shortest path that minimizes the movement path to the destination or a safety path that minimizes the possibility of collision with surrounding obstacles.
  • the safe path is more important for robotic applications, but the most ideal path will be the safest and the shortest possible path.
  • an obstacle detection sensor (a device that can measure the distance to surrounding obstacles such as laser, ultrasonic, etc.) is used to find the direction with the most empty space and to find the direction of the destination.
  • the weight of the direction toward the empty space and the direction toward the destination is determined experimentally. If a lot of weight is given to the empty space, the possibility of collision with an obstacle can be minimized, but in extreme cases, the destination may not be reached. Conversely, if you give a lot of weight to the destination, safety is poor.
  • the basic driving capability that an autonomous robot must have is intelligent navigation capability that can move to the desired target point in an optimal path without collision, and path planning technology and location recognition element technology are required for such intelligent navigation.
  • the route planning technology can be divided into global route planning and local route planning technology.
  • global route planning is to search for the optimal route from the starting point to the target point using a given environment map
  • Local route planning means creating an actual movement trajectory to avoid a dynamic obstacle recognized by a sensor.
  • the location recognition technology is a positioning technology that finds out the current position of a robot on a map while driving.
  • the Dijkstra algorithm described above has been suggested as the first route plan and has been widely used in various fields until now, but has a disadvantage in that it requires a lot of computation time since it searches all spaces.
  • the A* algorithm is a complementary form of the Dijkstra algorithm, and by adding an appropriate evaluation function, it is possible to achieve a faster search time than the Dijkstra algorithm based on the depth search and the area search.
  • the local path planner follows the path created by the global path plan given to the robot based on the current state of the robot and the local environment information, so that the path can be moved to avoid collisions caused by non-environmental obstacles. It's a planning skill.
  • Regional route planning is an essential technology for a mobile robot to move to a destination without obstacles and collisions in a daily space where environmental changes inevitably occur, and unlike the global route planning, real-time is required.
  • the above incremental (progressive) planning method can be calculated quickly, but if the distance between waypoints is short or the angle between waypoints is small, the path to the next target waypoint after the robot passes the target waypoint increases. There is a problem with this occurring.
  • Korean Patent Registration [10-1079197] discloses a route tracking method for an autonomous driving device.
  • the present invention was conceived to solve the above-described problems, and an object of the present invention is to determine a waypoint on the side of the robot traveling direction outside the sensor sensing area of the robot as a target waypoint, and if an overrun phenomenon does not occur
  • it provides a real-time waypoint route improvement method that enables autonomous driving by finding a more challenging and more optimized route, a recording medium storing a program for implementing it, and a computer program stored in the medium to implement the method.
  • a method for improving a real-time waypoint path in a method for improving a real-time waypoint path in the form of a program executed by an arithmetic processing means including a computer,
  • the waypoint path determination step (S10) among the local visible position space, which is a set of areas in which the arithmetic processing means does not have obstacles and collisions when moving straight from the robot among the movable areas detected by the robot sensors.
  • the waypoint pass segment connecting the local goal and the previous waypoint from the current position of the moving object to the nearest obstacle from the local goal enters the local goal accessible pass segment. It is characterized by planning a route to do.
  • the route planning step (S30) is characterized in that the route is planned by planning an accessible waypoint, which is a temporary waypoint to enter the local goal accessible pass segment.
  • the point where the distance to the local goal is the shortest among the local goal accessible pass segments is the accessible way point. It is characterized in that it is determined by.
  • the path planning step (S30) when there is an obstacle on the local bone accessible path segment, a temporary way to the direction side where there is no obstacle on the local visible position space so that there is no collision with the obstacle on the path between the local waypoints. It is characterized by planning a local waypoint, which is a point, and planning an accessible waypoint at a point after passing an obstacle on the local goal accessible pass segment, and planning a route through the local waypoint and the accessible waypoint. To do.
  • the cost of the local way point and the accessible way point is the smallest, and the local way point and the accessible way point are set. It is characterized.
  • the path planning step (S30) is characterized in that when there is an obstacle on the local bone accessible path segment, a local waypoint at which the angle formed with the current traveling direction of the robot is minimum is set.
  • a computer-readable recording medium in which a program for implementing the real-time waypoint path improvement method is stored is provided.
  • a program stored in a computer-readable recording medium is provided.
  • a recording medium storing a program for implementing the same, and a computer program stored in the medium to implement the same, the waypoint on the side of the robot traveling direction outside the sensor sensing area of the robot
  • the robot can more challengingly find a more optimized path to enable autonomous driving, thereby minimizing the occurrence of overrun of the robot and at the same time reducing the amount of computation, thus enabling real-time path calculation.
  • time coordination safety area By calculating the path based on, there is an effect of further reducing the amount of computation required for calculating the path.
  • a waypoint setting step, a reverse path calculation step, a forward path calculation step, and a robot control command generation step are performed, but by performing the reverse path calculation step before the forward path calculation step, the path is made to pass the target waypoint more smoothly. There is an effect that can be formed.
  • connection path connecting the forward path and the reverse path there is an effect of being able to connect the forward path and the reverse path so as not to put an excessive force on the robot.
  • connection path check step between the backward path calculation step and the forward path calculation step, there is an effect of further reducing the amount of computation required for path calculation.
  • connection path if there is a connection path, the forward time index for the connection path and the reverse path is set, and collision with dynamic obstacles of the connection path and the reverse path that were not considered in the calculation can be checked, thereby enabling faster and more stable path creation. have.
  • FIG. 1 is a flowchart of a method for improving a real-time waypoint route according to an embodiment of the present invention.
  • FIG. 2 is an exemplary view for explaining a local workspace applied to a method for improving a real-time waypoint route according to an embodiment of the present invention.
  • FIG 3 is an exemplary diagram for explaining a local position space applied to a method for improving a real-time waypoint route according to an embodiment of the present invention.
  • FIG. 4 is an exemplary view illustrating a local visible position space applied to a method for improving a real-time waypoint path according to an embodiment of the present invention.
  • FIG. 5 is an exemplary view for explaining a process of determining a local goal in a local goal determination step of a method for improving a real-time waypoint path according to an embodiment of the present invention.
  • FIG. 6 is an exemplary view for explaining a local goal accessible pass segment applied to a method for improving a real-time waypoint path according to an embodiment of the present invention.
  • FIG. 7 is an exemplary diagram for explaining a local waypoint and an accessible waypoint applied to a method for improving a real-time waypoint route according to an embodiment of the present invention.
  • FIG. 8 is a flowchart of an online bidirectional route planning method in a time state domain according to an embodiment of the present invention.
  • FIG. 9 is a flowchart of an online bidirectional route planning method in a time state domain according to another embodiment of the present invention.
  • FIG. 10 is a flowchart of an online bidirectional route planning method in a time state domain according to another embodiment of the present invention.
  • 11 is an exemplary view showing an example of calculating a route in real time according to a movement of a robot to which a method for improving a real-time waypoint route according to an embodiment of the present invention is applied.
  • FIG. 12 is an exemplary view showing a path the robot moves as a result of the path calculation of FIG. 11.
  • 13 is an exemplary view showing a simulation result in a place where the door is opened and closed.
  • FIG. 14 is an exemplary view showing a simulation result changed according to an update of sensing data and a path calculation period.
  • 15 is an exemplary view showing an autonomous driving simulation result according to a general route plan to which the present invention is not applied.
  • 16 is an exemplary view showing an autonomous driving simulation result according to a route plan to which a real-time waypoint route improvement method according to an embodiment of the present invention is applied.
  • connection path check step S35 forward path calculation step
  • FIG. 1 is a flowchart of a method for improving a real-time waypoint route according to an embodiment of the present invention
  • FIG. 2 is an exemplary view for explaining a local workspace applied to a method for improving a real-time waypoint route according to an embodiment of the present invention
  • 3 is an exemplary diagram for explaining a local position space applied to a real-time waypoint route improvement method according to an embodiment of the present invention
  • FIG. 4 is a real-time waypoint route improvement method according to an embodiment of the present invention.
  • FIG. 5 is an exemplary diagram for explaining a process of determining a local goal in a local goal determination step of a method for improving a real-time waypoint path according to an embodiment of the present invention
  • 6 is an exemplary view for explaining a local bone accessible pass segment applied to a method for improving a real-time waypoint path according to an embodiment of the present invention
  • FIG. 7 is a real-time waypoint according to an embodiment of the present invention.
  • FIG. 8 is a flowchart of an online two-way route planning method in a time state domain according to an embodiment of the present invention
  • FIG. 9 Is a flowchart of an online bidirectional route planning method in a time state domain according to another embodiment of the present invention
  • FIG. 10 is a flowchart of an online bidirectional route planning method in a time state domain according to another embodiment of the present invention.
  • 11 is an exemplary view showing an example of calculating a route in real time according to the movement of a robot to which the real-time waypoint route improvement method of the present invention is applied
  • FIG. 12 is an exemplary view showing the route traveled by the robot as a result of calculating the route of FIG.
  • FIG. 13 is an exemplary view showing a simulation result in a place where a door is opened and closed
  • FIG. 14 is an exemplary view showing a simulation result that changes according to an update of sensing data and a path calculation period
  • FIG. 15 is a view to which the present invention is not applied.
  • Fig. 16 is an exemplary diagram showing the result of an autonomous driving simulation according to a general route plan
  • FIG. 16 is a real-time waypoint view This is an example diagram showing the results of the autonomous driving simulation according to the route plan to which the route improvement method was applied.
  • a method for improving a real-time waypoint path includes a method for improving a real-time waypoint path in the form of a program executed by an operation processing means including a computer. It includes a determination step (S10), a local goal determination step (S20), a path planning step (S30), and a robot control step (S40).
  • Waypoints refer to points that the robot can designate as a target for driving, and are indicated as dots in the drawing. Targeting can pass through a waypoint, but you can also pass nearby without passing through.
  • the waypoint pass segment refers to a path connecting the waypoint and the waypoint.
  • the waypoint pass segment may be a line segment connecting a point (waypoint) and a point (waypoint), but may also be a curved line.
  • the waypoint path segment is a relatively safe path that does not collide with obstacles on the map. In other words, it is a path that does not collide with a fixed obstacle displayed on the map.
  • the waypoint path refers to a set of waypoint path segments that form an optimal path to a target point. That is, the waypoint path is a path consisting of waypoint path segments to a target point, and may be a set of line segments.
  • Local workspace refers to a workspace (area) based on sensor data (see Fig. 2).
  • the local workspace includes the local free workspace, the local opstarkle workspace, and the local unknow workspace.
  • Local Free Workspace Denotes a workspace without obstacles detected by the sensor, and corresponds to the area indicated by the orange side of FIG. 2.
  • Local Opstarkle Workspace Denotes a workspace limited to an obstacle detected by a sensor, and corresponds to an area indicated by a purple line segment in FIG. 2.
  • Local Unknow Workspace Denotes a workspace where collision with an obstacle cannot be predicted because it is an area not detected by a sensor, and corresponds to an area without color in FIG. 2.
  • the local position space refers to a workspace (area) based on sensor data in consideration of collisions according to the shape of the robot (see Fig. 3).
  • the local position space includes a local obscuring position space, a local preposition space, a local unknown position space, and a local visible position space.
  • Local Obstacle Position Space Is the obstacle area detected by the sensor It refers to a workspace that collides with and corresponds to the orange area of FIG. 3.
  • Local preposition space Denotes a workspace that does not collide with an obstacle detected by the sensor, and corresponds to the light blue area of FIG. 3.
  • Local Unknown Position Space Denotes a workspace where collision cannot be predicted because it is not detected by a sensor, and corresponds to an area without color in FIG. 3.
  • Local Visible Position Space Denotes a set of areas (spaces) without obstacles and collisions when the robot moves straight from the current position of the robot, and corresponds to the red area of FIG. 4.
  • Local Goal Accessible Pass Segment Denotes an area in which the local goal can be accessed directly to the local goal without collision with an obstacle among the waypoint pass segments connecting the local goal and the previous waypoint, and corresponds to the area indicated by the purple line segment of FIG. 6.
  • the calculation processing means determines a waypoint path, which is a set of waypoint path segments that form an optimal path to a target point among waypoint path segments that connect the waypoint and the waypoint. .
  • the waypoint path determination step (S10) determines an optimal path to which waypoints are connected based on the previously input map information.
  • the waypoint path can be regarded as an initial path, but it should be noted that the robot does not follow the waypoint path.
  • the waypoint path is only information that is referenced to find an optimal route.
  • the local bone determination step (S20) is a local visible position space that is a set of areas without obstacles and collisions (on the map) when the operation processing means moves straight from the robot among the movable areas of the robot detected by the sensor of the robot. Among them, the next waypoint of the last waypoint on the waypoint path determined in the waypoint path determination step S10 or the next waypoint of the waypoint path segment is determined as a target waypoint, a local goal.
  • the local visible position space is narrower than the local preposition space.
  • the local visible position space is displayed in red and the local pre-position space is displayed in light blue.
  • a method for improving a real-time waypoint path according to an embodiment of the present invention is for a more challenging robot to find a more optimized path
  • the robot calculates the path based on the detected information.
  • the robot when the robot falls on the waypoint path for reasons such as avoiding obstacles, the robot can designate a local goal at a certain point based on the result recognized by the robot, and plan a path based on the local goal.
  • a local goal is determined on the basic waypoint path and a path (pass) to go toward the local goal is planned.
  • Local Visible Position Space is meaningful because it is safe to go straight on the Local Visible Position Space when trying to improve a previously planned route (refining the route), so it is good to take the first waypoint.
  • the waypoint at the rear of the waypoints that can safely go straight may be determined as a local goal, but it is not challenging and is not considered, and a waypoint is placed on an invisible area, that is, a local unknown position space I thought about taking pictures,
  • the last waypoint that can be checked on the local visible position space or the next waypoint of the waypoint pass segment is determined as a local goal.
  • the path can be planned toward the point closest to the local goal without collision with the obstacle on the local goal accessible path segment on the local unknown position space.
  • the next waypoint of the last waypoint on the waypoint path or the next waypoint of the waypoint path segment is determined as a target waypoint, a local goal.
  • the local goal determination step S20 determines the next waypoint of the last waypoint corresponding to the intersection of the local visible position space and the waypoint path as a local goal.
  • the next waypoint of the last waypoint that can be checked may be determined as the local goal.
  • the operation processing means plans a path from the position of the robot to the local bone determined in the local bone determination step S20.
  • The'time state domain' refers to a set of state values considered for time.
  • The'status value' refers to a value that includes a coordinate value for a position and azimuth (heading angle, etc.) and includes any one or more information selected from among steering angle, speed (linear velocity, angular velocity), and acceleration. For example, it may be (x-coordinate, y-coordinate, bearing, velocity, acceleration).
  • Time coordination region' refers to a set of coordination values considered for time.
  • 'Coordination value' refers to a value including a position and azimuth (heading angle, etc.). For example, it may be (x coordinate, y coordinate, direction).
  • the status value of the robot's current position is marked as's k ',
  • the state value calculated by f step from the current position of the robot in the forward path is expressed as's f '.
  • the status value of the robot is marked as'g w '.
  • step b The status value calculated by step b from the current target waypoint to the reverse path is expressed as's -b ',
  • the robot's status value is expressed as's' (lowercase s),
  • the status area which is a set of robot status values, is marked with'S' (capital S),
  • the time state value which is the state value at time step n, is expressed as s n (lowercase s),
  • the time-state domain is denoted as'S n '(s n ⁇ S n ),
  • the coordination area which is a set of coordination values of the robot, is marked with'Q' (capital Q),
  • the time coordination value which is the coordination value at time step n, is expressed as q n (lowercase q),
  • the temporal coordination domain is denoted as'Q n '(q n ⁇ Q n ),
  • the coordination area that collides with a static obstacle is' ', and
  • the route planning step (S30) of the real-time waypoint route improvement method plans a two-way route that gradually plans (calculates) the forward route and the reverse route, and is used to plan the forward route and the reverse route.
  • the state value (s n (n is a time index, a natural number)) in the time state area is selected from the steering angle, speed (linear speed, angular speed), and acceleration including the coordinate values for the position and azimuth (heading angle). It may be characterized by including any one or a plurality of information.
  • Forward path calculation calculates the forward path in the time state domain considering the state value (s) and the time value from the current position of the robot or the last calculation point of the forward path to the current target waypoint or the last calculation point of the reverse path. .
  • the time value is a value that can check the time from the current time to the future, and can be used only as a time index (n), but the calculation period for calculating one step is multiplied by the time index (n) (calculation period *
  • the time index (n) available.
  • the forward path calculation may calculate a forward path in a time state domain from the current position of the initial robot toward the current target waypoint. After that, if the forward path and the reverse path are calculated, the forward path in the time state domain from the last calculation point of the forward path to the last calculation point of the reverse path can be calculated.
  • the reverse path in the time state domain from the current target waypoint or the last calculation point of the reverse path to the current position of the robot or the last calculation point of the forward path is calculated.
  • a reverse path in a time state region from an initial current target waypoint to a current position of the robot may be calculated. After that, if the forward path and the reverse path are calculated, the forward path in the time state domain from the last calculation point of the reverse path to the last calculation point of the forward path is calculated.
  • the forward path calculation and the reverse path calculation are planned to face the last calculation point on the opposite side.
  • Planning the reverse path is to make the robot pass more smoothly when it passes the target waypoint, so that if the distance between waypoints is short or the angle between waypoints is small, the robot passes the target waypoint and then moves toward the next target waypoint. This is to reduce the overrun phenomenon in which the turning path becomes larger.
  • the state value (s n ) is at a given point. It may be characterized by obtaining a state value (s n+m ) at a step that will proceed as much as the number of steps (m) to be calculated toward the target point (s to ).
  • the forward path calculation and the reverse path calculation can be defined as follows.
  • the robot's input value u n can be obtained as follows.
  • Is a cost function that returns a cost value that occurs when the transition to s n + m to the given mobile cost function by using the input u which the status of the robot in a s n on the input for the least effort.
  • U n that minimizes is an input value that can change the robot to the target state value with minimal effort.
  • H r is arranged in the dominant order. In other words, H r with smaller r is more dominant.
  • H r is arranged in the dominant order. In other words, H r with smaller r is more dominant.
  • Time-state safety zone minimizing the r part from H 1 to H r can be defined as:
  • Time-state safe area calculated as an unresolved movement cost function Is the time state safety zone Is the same as
  • s n +m is the state value at n+m steps
  • N is the approximate optimal time state value calculation function
  • s n is the given state value at n steps
  • s to is the state value at the target point
  • m is Number of steps you want to calculate
  • the robot state value of s n is the current state in order to transition to the state of s to, n after the optimum status of the m-th time index s It is calculated as n+m .
  • H 1 is the speed-reading independent movement cost function
  • H 2 is the angle-travel direction partial cost function
  • H 3 is the velocity magnitude partial movement cost function
  • the movement cost function H(s from , s to ) can be composed of three parts, and D is a predefined threshold distance.
  • each time state is determined based on the velocity independent movement cost function H 1 .
  • the direction of movement partial movement cost function H 2 and the velocity magnitude partial movement cost function H 3 are used to set the state of the current target waypoint.
  • each time setting is determined to be closest to the target.
  • H 2 and H 3 are designed to set the current target waypoint state.
  • the speed at the current target waypoint is determined in consideration of the position of the robot, the position of the target waypoint, and the position of the next waypoint.
  • the direction is determined as the average direction of the two vectors to the position of the robot, the position of the target waypoint, and the position of the target waypoint and the position of the next waypoint.
  • the size of the speed at the target waypoint is determined according to the inner angle of the path at the target waypoint.
  • the current speed of the target waypoint is set in proportion to the distance so that it does not vibrate near the waypoint.
  • H 1 is the speed-reading independent movement cost function
  • H 2 is the angle-travel direction partial cost function
  • H 3 is the velocity magnitude partial movement cost function
  • each time state is determined based on a speed-independent movement cost function H 1 .
  • H 1 In order to consider both the position close to the target position and the direction toward the target position, H 1 consists of two parts with a predefined weight ⁇ .
  • the movement direction partial movement cost function H 2 and the velocity magnitude partial movement cost function H 3 are used to set the linear and angular velocity of the current target waypoint in a manner similar to the example of a robot capable of omnidirectional movement.
  • the forward route calculation of the online bidirectional route planning method in the time state domain is a time coordination safety area, which is a safe area on the coordination area that does not collide with static and dynamic obstacles. If is present, the coordination value of the robot at the time index (n) ( ) And time index (n) It characterized in that it calculates the forward path based on,
  • the coordinate value of the robot at the time index (n) ( ) And time coordination safety zone It may be characterized by calculating the reverse path based on.
  • the robot can predict the path of each dynamic obstacle such as humans and other robots based on a tracking algorithm using sensor data.
  • the free dynamic coordination region at time index n Is a safe area for robots that do not collide with obstacles including dynamic obstacles and static obstacles in time index n.
  • the motion of the robot system with the input value u n (u n ⁇ U) of the robot at the time index n can be defined as follows.
  • Environmental detectors detect and track obstacles based on a sensor system using sensors such as vision sensors or laser range finders (LRF), and classify them into static obstacles (environmental obstacles) and dynamic obstacles (non-environmental obstacles). And Can be obtained.
  • sensors such as vision sensors or laser range finders (LRF)
  • LRF laser range finders
  • the global route planner which plans routes by assigning waypoints, Plan a series of waypoints and goals inside.
  • the robot sequentially passes through the waypoints and And You can use to plan a path to reach your goal without collision.
  • the reachable time state region at the time index n + m can be defined, and at this time, the reachable time coordination region can also be defined.
  • the robot can be controlled with a uniform input value of the robot over m time steps.
  • the reachable time state area accessible by the uniform input value of the robot can be defined as follows.
  • an area approximating the time coordination area reachable by the uniform input value of the robot may be defined as follows.
  • a safe time-state safe area at time index n + m can be defined as:
  • the safe time coordination safe area at time index n + m can be defined as:
  • the route planning step (S30) of the real-time waypoint route improvement method includes a waypoint setting step (S32), a reverse path calculation step (S33), and a forward path calculation step. It may include (S35).
  • the waypoint setting step S32 sets the state of the robot at the current target waypoint.
  • the current target waypoint is the waypoint the forward trajectory is heading to pass.
  • the waypoint setting step (S32) is to set the state of the robot when the robot passes the current target waypoint, and considers the position of the robot, the position of the target waypoint, and the position of the next waypoint. It is desirable to set the robot's state when the robot passes the point.
  • the waypoint setting step (S32) is characterized in that the current target waypoint is a waypoint to which the forward path is headed, and a state value (g w ) of the current target waypoint that can minimize the moving cost as shown in the following equation is set. can do.
  • the reverse path calculation step (S33) calculates the reverse path.
  • a route is planned from the current target waypoint toward the current position of the robot. At this time, if the forward path is calculated, the reverse path toward the last calculation point of the forward path can be calculated.
  • variable B indicated in the conditional sentence of FIG. 8 is the maximum value of the time step for the reverse route planning, and the variable b means the time step of the reverse route plan (increases by 1 when repetitive calculations are made), but the variable and conditions for it are arbitrarily set Of course, it can be used in various ways. (The same applies to the variables of FIGS. 9 to 10)
  • the forward path is calculated.
  • a path is planned from the current position of the robot toward the target waypoint. At this time, if the reverse route is calculated, the forward route toward the last calculation point of the reverse route can be calculated.
  • variable F indicated in the conditional sentence of Fig. 8 is the maximum value of the time step for forward path planning
  • variable f is the time step of the reverse path plan (increases by 1 when calculating iteratively)
  • k is the current time step.
  • the reverse path calculation step (S33) and the forward path calculation step (S35) may be performed by reversing the order, but first performing the reverse path calculation step (S33) allows the path to pass more smoothly through the target waypoint. Can be formed, it is preferable to first perform the reverse path calculation step (S33).
  • the reverse path calculation step (S33) and the forward path calculation step (S35) may be repeatedly performed alternately, and the reverse path calculation step (S33) or the forward path calculation step (S35) is first repeated a certain number of times.
  • the forward path calculation step (S33) and the forward path calculation step (S35) may be repeatedly performed in various ways, such as repeating the forward path calculation step (S35) or the reverse path calculation step (S33). .
  • the two-way path planning from the current position to the current target waypoint is completed only when the reverse path and the forward path are connected.
  • a connection route connecting the forward route and the reverse route is calculated, and a bidirectional route for gradually planning a forward route and a reverse route is calculated. It can be characterized by planning.
  • the forward route and the reverse route may meet, but the speed may be different.
  • connection path in order to overcome the difference in speed between the forward path and the reverse path, it is preferable to be connected by the connection path.
  • connection path connected to the forward path side is calculated to have the same speed as the last calculation point of the forward path
  • the other side of the connection path connected to the reverse path side has the same speed as the last calculation point of the reverse path. It is desirable to calculate the connection path so that it is possible.
  • connection path which is the section between the last calculated state value s f of the forward path and the last calculated state value s -b of the reverse path, equalizes the input value of the robot and is calculated as follows: It can be characterized by that.
  • f(a, b, c) is a motion model function of the robot that calculates the state value of the robot that is moved to the input value of the robot b by c time steps at the point corresponding to the state value a.
  • the path planning step (S30) of the real-time waypoint path improvement method includes a waypoint setting step (S32), a reverse path calculation step (S33), and a connection It may include a path check step (S34) and a forward path calculation step (S35).
  • the waypoint setting step S32 sets the state of the robot at the current target waypoint.
  • the current target waypoint is the waypoint the forward trajectory is heading to pass.
  • the waypoint setting step (S32) is to set the state of the robot when the robot passes the current target waypoint, and considers the position of the robot, the position of the target waypoint, and the position of the next waypoint. It is desirable to set the robot's state when the robot passes the point.
  • the current target waypoint is the waypoint to which the forward path is directed, and the following equation
  • a state value (g w ) of a current target waypoint that can minimize moving cost may be set.
  • the reverse path calculation step (S33) calculates the reverse path.
  • a route is planned from the current target waypoint toward the current position of the robot. At this time, if the forward path is calculated, the reverse path toward the last calculation point of the forward path can be calculated.
  • the reverse path may be calculated step by step or may be calculated in a predetermined step unit.
  • step S34 of checking the connection path it is checked whether there is a connection path in which the current position of the robot or the last calculation point of the forward path and the current target waypoint or the last calculation point of the reverse path are connected.
  • connection path checking step (S34) may be performed each time the reverse path is calculated by one step, or may be performed each time the reverse path is calculated by a predetermined number of steps.
  • connection path check step (S34) If there is a connection path, it may be characterized in that the return to the waypoint setting step (S32).
  • Planning the reverse path ahead of the forward path allows the robot to pass more smoothly when it passes the target waypoint. If the distance between waypoints is short or the angle between waypoints is small, the robot passes the target waypoint and then the next target way. This is to reduce the overrun phenomenon in which the path turning toward the point becomes larger.
  • calculating the reverse path first by a predetermined number of times is also to make it smoother when the robot passes the target waypoint.
  • the reverse path calculation step (S33) to the connection path check step (S34) is repeatedly performed a predetermined number of times, the next step may be performed even if the connection path does not exist.
  • a path is planned from the current position of the robot toward the target waypoint. At this time, if the reverse route is calculated, the forward route toward the last calculation point of the reverse route can be calculated.
  • the forward path may be calculated step by step, or may be calculated in a predetermined step unit.
  • connection path checking step (S34) of the method for online bidirectional path planning in a time state domain if a connection path exists, a forward time index for the connection path and the reverse path is set, and the connection path And after checking whether an inevitable collision condition occurs in the reverse path, if the inevitable collision condition does not occur, the time variable of the forward route, the time variable of the reverse route, and the time variable of the forward route passing through the next waypoint are calculated and changed. You can do it.
  • the forward time index applied to the forward path can know the absolute time (time based on the robot). Thus, it is possible to predict the collision of a dynamic obstacle.
  • the time index used for the link path and the reverse path must be changed to the forward time index applied to the forward path in order to check the collision of dynamic obstacles. You can know the absolute time of the route and the reverse route, and check whether there is a predicted collision in the reverse route and the connection route.
  • the robot control step (S40) controls the movement of the robot by calculating a command for controlling the robot according to the path planned in the path planning step (S30).
  • a command for controlling the robot may be calculated according to the bidirectional path.
  • a command for controlling the robot may be calculated according to the bidirectional path (see FIG. 9).
  • the input value of the robot generated in the robot control step S40 may be calculated as follows.
  • the path planning step (S30) of the real-time waypoint path improvement method is an obstacle closest to the local goal in the waypoint path segment connecting the local goal and the previous waypoint from the current position of the moving object. It may be characterized by planning a route to the local goal accessible pass segment, which is an area to.
  • the local goal accessible pass segment refers to an area in which the local goal can be accessed directly to the local goal without collision with obstacles among the waypoint pass segments connecting the local goal and the previous waypoint. If there is no obstacle on the waypoint pass segment connecting the previous waypoint, the entire waypoint pass segment connecting the local goal and the previous waypoint becomes the local goal accessible pass segment (the purple line segment indicated by the arrow),
  • the safest place in the local unknow position space is the waypoint pass segment
  • the area in which the waypoint path can be directly safely accessed to the local goal is determined as the local goal accessible pass segment.
  • the route planning step (S30) of the real-time waypoint route improvement method according to an embodiment of the present invention is characterized in that the route is planned by planning an accessible waypoint, which is a temporary waypoint to enter the local goal accessible path segment. can do.
  • the local goal (W M ) is determined on the intersection of the waypoint pass and the local unknown position space, and the temporary waypoint (W m , m) before entering the local goal (W M ) is A natural number) should be decided on the local goal accessible pass segment.
  • the local visible position space and the local bone accessible path when there is an intersection of the local visible position space and the local bone accessible path segment, the local visible position space and the local bone accessible path It may be characterized in that the point at which the specific cost function is minimized within the intersection with the segment is determined as an accessible waypoint.
  • the specific cost function refers to a cost function calculated in consideration of time, distance, speed, acceleration, energy consumption, and the like.
  • the local visible position space and the local bone accessible path when there is an intersection of the local visible position space and the local bone accessible path segment, the local visible position space and the local bone accessible path It may be characterized in that the point where the movement distance from the robot to the local goal is shortest within the intersection with the segment is determined as the accessible waypoint.
  • W 1 indicated by an arrow may be an accessible waypoint.
  • plan a local waypoint which is a temporary waypoint toward the direction of travel without obstacles on the local visible position space, and plan an accessible waypoint at the point after passing the obstacle on the local visible position space. It can be characterized by planning a route through points and accessible waypoints.
  • W 1 indicated by an arrow may be a local waypoint, and W 2 may be an accessible waypoint.
  • a local waypoint is determined in the direction toward the local visible position space, and an accessible waypoint is determined on the local goal accessible path segment. You can plan.
  • the route planning step (S30) of the method for improving a real-time waypoint route according to an embodiment of the present invention is, when there is no intersection between the local visible position space and the local goal accessible path segment, the local waypoint and the accessible waypoint are It can be characterized by setting a local waypoint and an accessible waypoint with the smallest cost (distance, etc.).
  • the safest area is the local visible position space
  • the next safe area is the local goal accessible path segment
  • the next safe area is the local unknown position space.
  • the distance moving within the local visible position space area and the distance moving within the local goal accessible pass segment area are increased, while the distance passing through the local waypoint and the accessible waypoint is increased. It is desirable to minimize it.
  • FIG. 11 shows an example of calculating a path in real time according to the movement of the robot. In the figure on the left, as time passes, the path changes as shown on the right.
  • the yellow radius in FIG. 11 shows the sensing range according to the movement of the robot.
  • the black dotted line in FIG. 12 shows the waypoint path.
  • the sensing data update and the path calculation period were set to 0.5 seconds, as shown in the lower right figure of FIG. 14, it was confirmed that the path was not a planned path but proceeded to a fast path that could shorten the path.
  • the blue dots shown in FIG. 14 represent the movement path of the robot.
  • FIG. 15 shows the results of an autonomous driving simulation according to a general route plan to which the present invention is not applied
  • FIG. 16 shows the results of an autonomous driving simulation according to a route plan to which the real-time waypoint route improvement method according to an embodiment of the present invention is applied. To show.
  • the current angle formed with the moving direction of the robot is minimal. It may be characterized by setting a local waypoint to be.
  • the distance and angle have been described as examples as items that can be considered as cost, but the present invention is not limited thereto, and the local waypoint is set so that the cost is minimized in consideration of the speed and time of the robot. It is possible, of course, that various implementations are possible, such as setting a local waypoint so that the cost is minimized in consideration of various items among them.
  • the above-described online bidirectional route planning method in the time state domain may be provided in a recording medium that can be read through a computer by tangibly implementing a program of instructions for implementing it.
  • a recording medium that can be read through a computer by tangibly implementing a program of instructions for implementing it.
  • the computer-readable recording medium may include a program command, a data file, a data structure, or the like alone or in combination.
  • the program instructions recorded on the computer-readable recording medium may be specially designed and constructed for the present invention, or may be known and usable to those skilled in computer software.
  • Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magnetic-optical media such as floptic disks, and ROM, RAM, and flash memory.
  • a hardware device specially configured to store and execute program commands such as USB memory, and the like.
  • Examples of the program instructions include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like.
  • the hardware device may be configured to operate as one or more software modules to perform the operation of the present invention, and vice versa.

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  • Engineering & Computer Science (AREA)
  • Robotics (AREA)
  • Mechanical Engineering (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
  • Manipulator (AREA)

Abstract

La présente invention concerne un procédé d'amélioration de trajet de point de cheminement en temps réel, un support d'enregistrement dans lequel un programme pour sa mise en oeuvre est stocké, et un programme informatique stocké dans un support pour sa mise en oeuvre, et plus particulièrement: un procédé d'amélioration de trajet de point de cheminement en temps réel, qui détermine, en tant que point de cheminement cible, un point de cheminement côté direction de déplacement de robot qui est à l'extérieur d'une région de détection de capteur d'un robot, de sorte que le robot peut se déplacer de manière autonome par la découverte plus active d'un trajet plus optimisé; un support d'enregistrement dans lequel est stocké un programme de sa mise en oeuvre; et un programme d'ordinateur stocké dans un support afin de le mettre en oeuvre.
PCT/KR2020/002360 2019-04-29 2020-02-19 Procédé d'amélioration de trajet de point de cheminement en temps réel, support d'enregistrement dans lequel est stocké un programme de mise en œuvre du procédé, et programme informatique stocké dans un support pour sa mise en œuvre WO2020222408A1 (fr)

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KR1020190049486A KR102097715B1 (ko) 2019-04-29 2019-04-29 실시간 웨이포인트 경로 개선 방법, 이를 구현하기 위한 프로그램이 저장된 기록매체 및 이를 구현하기 위해 매체에 저장된 컴퓨터프로그램

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