CN111168681B - Mechanical arm intelligent obstacle avoidance method and system for man-machine safety interaction and robot - Google Patents
Mechanical arm intelligent obstacle avoidance method and system for man-machine safety interaction and robot Download PDFInfo
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- CN111168681B CN111168681B CN202010027287.2A CN202010027287A CN111168681B CN 111168681 B CN111168681 B CN 111168681B CN 202010027287 A CN202010027287 A CN 202010027287A CN 111168681 B CN111168681 B CN 111168681B
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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
- B25J9/1674—Programme controls characterised by safety, monitoring, diagnostic
- B25J9/1676—Avoiding collision or forbidden zones
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/008—Manipulators for service tasks
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J5/00—Manipulators mounted on wheels or on carriages
- B25J5/007—Manipulators mounted on wheels or on carriages mounted on wheels
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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
- B25J9/1666—Avoiding collision or forbidden zones
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/39—Robotics, robotics to robotics hand
- G05B2219/39082—Collision, real time collision avoidance
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/39—Robotics, robotics to robotics hand
- G05B2219/39091—Avoid collision with moving obstacles
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/40—Robotics, robotics mapping to robotics vision
- G05B2219/40202—Human robot coexistence
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/40—Robotics, robotics mapping to robotics vision
- G05B2219/40411—Robot assists human in non-industrial environment like home or office
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- Engineering & Computer Science (AREA)
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- Mechanical Engineering (AREA)
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Abstract
The invention provides a mechanical arm intelligent obstacle avoidance method, a mechanical arm intelligent obstacle avoidance system and a robot for man-machine safety interaction, wherein the robot monitors an identification code on an obstacle in real time through an identification code visual positioning method to obtain the position of the obstacle; calculating the motion state of the obstacle according to the position detection result and the position change of the obstacle, and adopting a corresponding obstacle avoidance strategy according to the motion state of the obstacle; the mechanical arm can make different obstacle avoidance strategies for obstacles in different motion states or human limbs, and compared with the existing obstacle avoidance method, the mechanical arm gets rid of the limitation of environment modeling, is high in planning speed, and can make timely and effective obstacle avoidance strategies for obstacles and dynamic obstacles which suddenly appear in a working space.
Description
Technical Field
The disclosure relates to the technical field of robot obstacle avoidance, in particular to a mechanical arm intelligent obstacle avoidance method and system for man-machine safe interaction and a robot.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the development of robotics and the rise of industry 4.0, human-computer interaction and human-computer cooperation are more and more concerned by people, and human-computer safety is the first problem to be solved in the interaction process.
The inventor of the present disclosure finds that, in terms of the existing anti-collision method, the dependence on the environment where the mechanical arm is located is large, and the premise of obstacle avoidance is that the obstacle in the environment is known and the modeling is completed, which determines that the method has long calculation time and is only suitable for a structured static scene, and cannot timely and effectively cope with the suddenly appearing obstacle in the working space or the dynamic obstacle with unknown movement law, which is also the reason that most mechanical arms work in an isolated fence at present.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an intelligent obstacle avoidance method, system and robot for a mechanical arm facing human-computer safe interaction, so that the mechanical arm can make different obstacle avoidance strategies for obstacles in different motion states or human limbs, the limitation of environment modeling is eliminated, the planning speed is high, and timely and effective obstacle avoidance strategies can be made for suddenly appearing obstacles and dynamic obstacles in a working space.
In order to achieve the purpose, the following technical scheme is adopted in the disclosure:
the first aspect of the disclosure provides an intelligent obstacle avoidance method for a mechanical arm oriented to man-machine safe interaction.
An intelligent mechanical arm obstacle avoidance method for man-machine safe interaction is characterized in that a robot obtains the position of an obstacle by monitoring marks on the obstacle in real time;
and calculating the motion state of the obstacle according to the position detection result and the position change of the obstacle, and adopting a corresponding obstacle avoidance strategy according to the motion state of the obstacle.
As some possible realization modes, the obstacle speed is calculated through the change of the obstacle position, and a speed influence factor is obtained and used for describing the obstacle motion state.
As some possible implementation manners, the robot monitors the identification code on the obstacle in real time through an identification code visual positioning method to obtain the position of the obstacle.
As some possible implementation manners, calculating a distance influence factor and a relative distance between the obstacle and a mechanical arm of the robot in real time through the detected obstacle position, wherein the distance influence factor is used for being introduced into a speed potential field to avoid that a speed repulsive force caused when the speed of the obstacle exceeds or is lower than a set threshold exceeds or is lower than the set threshold;
judging whether the mechanical arm of the robot enters the influence range of the obstacle in real time according to the relative distance, and if the mechanical arm of the robot enters the influence range, implementing an obstacle avoidance strategy; otherwise, the artificial potential field moves under the action of the gravitational potential field.
As a further limitation, the mechanical arm determines whether it is a fast obstacle or a slow or stationary obstacle according to the magnitude of the speed influence factor.
As a further limitation, for a fast obstacle, the obstacle avoidance from the rear of the obstacle speed is specifically as follows: according to an artificial potential field method and the influence of a velocity potential field, the current resultant force direction of the mechanical arm is determined, position sampling is carried out in the reverse direction of the Z-axis component (namely, the vertical component) of the barrier velocity, and the position point with the highest evaluation function is selected as the position of the next moment.
As a further limitation, the current resultant force applied to the mechanical arm specifically includes:
Ftotal＝Fatt+Frep+Fvel
wherein, Fatt，Frep，FvelRespectively representing the attractive, repulsive and velocity repulsive forces experienced by the obstacle.
As a further limitation, for an obstacle with a slow moving speed or a standstill, the obstacle is avoided in the direction of the obstacle speed or above the obstacle location point.
As some possible implementation manners, the adaptive step setting is realized by increasing or decreasing the relative distance between the obstacle and the tail end of the mechanical arm of the robot and the change of the relative distance, specifically:
when the relative distance is reduced, based on the current relative distance and relative speed, and taking the influence radius of the dynamic obstacle as a reference, obtaining the longest time that the mechanical arm can move;
when the relative distance is smaller than or equal to the obstacle influence radius, sampling by adopting a fixed step length smaller than a set threshold value so as to reduce the collision probability;
when the relative distance is larger than the obstacle-influencing radius and the relative distance is increasing, the target point is directly selected as the next position point.
The second aspect of the disclosure provides a mechanical arm intelligent obstacle avoidance system for man-machine safe interaction, which comprises at least one robot with a mechanical arm and at least one obstacle provided with an identification code, wherein the robot carries out obstacle avoidance by using the mechanical arm intelligent obstacle avoidance method for man-machine safe interaction of the first aspect of the disclosure.
The third aspect of the disclosure provides a robot for human-computer safe interaction, and the robot utilizes the intelligent obstacle avoidance method for the mechanical arm for human-computer safe interaction to avoid obstacles.
Compared with the prior art, the beneficial effect of this disclosure is:
1. the mechanical arm can make different obstacle avoidance strategies for obstacles in different motion states or human limbs, and compared with the existing obstacle avoidance method, the mechanical arm gets rid of the limitation of environment modeling, is high in planning speed, and can make timely and effective obstacle avoidance strategies for obstacles and dynamic obstacles which suddenly appear in a working space.
2. The method and the device have the advantages that the mechanical arm can adopt corresponding effective obstacle avoidance strategies for obstacles in different motion states through real-time obstacle detection in an unstructured and dynamic environment, and the man-machine safety is ensured; through self-adaptive step length setting, the efficiency of planning a path by the mechanical arm is improved
3. The method and the device judge whether the mechanical arm enters the influence range of the obstacle in real time according to the relative distance, if the mechanical arm enters the influence range, an obstacle avoidance strategy is implemented, otherwise, the mechanical arm moves under the action of the gravitational potential field in the artificial potential field, and the man-machine safety is further improved.
4. According to the method, the distance influence factor is introduced into the speed potential field, so that the phenomenon that the speed repulsion force is too large or too small due to too large or too small obstacle speed is avoided, and the obstacle avoidance accuracy is improved.
Drawings
Fig. 1 is a schematic diagram of an experimental platform and a method test provided in embodiment 1 of the present disclosure.
Fig. 2 is a schematic diagram of a position sampling strategy under a 2D view angle provided in embodiment 1 of the present disclosure.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
Example 1:
in order to combine the human coordination and cognitive judgment capability with the advantages of the precision and repetitive work of the mechanical arm, the mechanical arm needs to share a working space with human and has the capability of cooperating with human colleagues side by side, so that the mechanical arm is determined to be capable of coping with the change of the environment, and intelligent and effective obstacle avoidance measures can be made according to the motion state of human limb actions to ensure the human-computer safety.
The embodiment 1 of the present disclosure provides an intelligent obstacle avoidance method for a mechanical arm facing human-computer safe interaction, where a robot monitors a two-dimensional code (as shown in fig. 1) on a human arm in real time through a two-dimensional code visual positioning technology, and then calculates a motion state of a human body according to a result and a change of obstacle position detection, where the obstacle avoidance method described in this embodiment may judge the motion state of an obstacle to adopt a corresponding obstacle avoidance strategy, and a specific obstacle avoidance process is as follows:
(1) calculation of the impact factor
The obstacle speed is deduced from the change of the obstacle position and used to calculate a speed influence factor, which is a flag describing the movement state of the obstacle.
The detected obstacle position is used for calculating the relative distance between the obstacle position and the mechanical arm and the distance influence factor in real time, and the distance influence factor is larger when the relative distance is shorter; by introducing a distance influence factor into the velocity potential field, the phenomenon that the velocity repulsion force caused by too large or too small barrier velocity is too large or too small is avoided.
And judging whether the mechanical arm enters the influence range of the obstacle or not in real time according to the relative distance, if so, implementing an obstacle avoidance strategy, and otherwise, moving under the action of the gravitational potential field in the artificial potential field.
(2) Calculation of obstacle avoidance strategies
The mechanical arm judges whether the obstacle is a fast obstacle or a slow or static obstacle according to the magnitude of the speed influence factor, wherein the fast obstacle is an obstacle larger than a first preset speed, and the slow obstacle is an obstacle smaller than a second preset speed;
for rapid obstacles, the current resultant force direction of the mechanical arm is determined according to an artificial potential field method and the influence of a velocity potential field.
The specific resultant force calculation formula is as follows:
Fatt＝ka(Xg-X) (1)
Ftotal＝Fatt+Frep+Fvel (4)
wherein, Fatt，Frep，FvelRespectively representing the attraction force, the repulsion force and the velocity repulsion force applied to the obstacle; k is a radical ofa，kr，kroIs a scale constant, kvAs a velocity influencing factor, XgX respectively represents a target position and the current position of the tail end of the mechanical arm; f. ofdAs a distance-influencing factor, p0In order for the obstacle repulsive force to affect the radius, p (X) is the relative distance between the mechanical arm and the obstacle at the current position X; alpha is the relative speed of the tail end of the mechanical arm and the obstacle and the included angle of the obstacle relative to the position vector of the mechanical arm.
After the current resultant force direction of the mechanical arm is obtained, combining the thought of a dynamic window, sampling the position in the reverse direction of the Z-axis component of the barrier speed, and selecting the position point with the highest evaluation function as the position of the next moment, namely, avoiding the barrier from the rear of the barrier speed; on the contrary, for an obstacle with slow moving speed or static moving speed, the obstacle is avoided in the positive direction of the obstacle speed or above the obstacle position point (as shown in fig. 2).
(3) Setting of sampling step size
The traditional artificial potential field method adopts equal step length to detect and plan a path, but in combination with reality, the step length can be properly increased under the condition of being far away from an obstacle, so that the path planning efficiency is improved.
In this embodiment, the adaptive step length setting is realized by increasing or decreasing the relative distance between the obstacle and the end of the mechanical arm and the change of the relative distance, specifically:
and under the condition that the relative distance is reduced, calculating the longest time that the mechanical arm can move by taking the influence radius of the dynamic obstacle as a reference on the basis of the current relative distance and the relative speed.
When the relative distance reaches the obstacle influence radius, namely the relative distance is smaller than or equal to the obstacle influence radius, sampling by adopting a fixed small step length to reduce the collision probability;
when the relative distance is larger than the obstacle influence radius and the relative distance is increasing, namely the obstacle is moving away, the target point can be directly selected as the next position point, so that the operation efficiency is improved.
According to the embodiment, the mechanical arm can adopt corresponding effective obstacle avoidance strategies for obstacles in different motion states through real-time obstacle detection in an unstructured and dynamic environment, so that the man-machine safety is ensured; the method gets rid of the limitation of environment modeling and graph building, and can effectively and timely react to sudden changes in the environment; through self-adaptive step length setting, the efficiency of planning the path by the mechanical arm is improved.
Example 2:
the embodiment 2 of the present disclosure provides an obstacle avoidance system for intelligent robot arm for human-computer safe interaction, which includes a robot with a robot arm and an obstacle posted with a two-dimensional code, wherein the robot employs the robot arm intelligent obstacle avoidance method for human-computer safe interaction according to the embodiment 1 of the present disclosure to avoid the obstacle.
Example 3:
the embodiment 3 of the present disclosure provides a robot for human-computer safe interaction, and the robot uses the intelligent mechanical arm obstacle avoidance method for human-computer safe interaction described in the embodiment 1 of the present disclosure to avoid obstacles.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Although the present disclosure has been described with reference to specific embodiments, it should be understood that the scope of the present disclosure is not limited thereto, and those skilled in the art will appreciate that various modifications and changes can be made without departing from the spirit and scope of the present disclosure.
Claims (8)
1. An intelligent mechanical arm obstacle avoidance method for man-machine safe interaction is characterized in that a robot obtains the position of an obstacle by monitoring an identifier on the obstacle in real time;
calculating the motion state of the obstacle according to the position detection result and the position change of the obstacle, and adopting a corresponding obstacle avoidance strategy according to the motion state of the obstacle;
calculating a distance influence factor and a relative distance between the obstacle and a mechanical arm of the robot in real time through the detected obstacle position, wherein the distance influence factor is used for being introduced into a speed potential field to avoid that speed repulsive force caused when the obstacle speed exceeds a set threshold or is lower than the set threshold exceeds the set threshold or is lower than the set threshold;
judging whether the mechanical arm of the robot enters the influence range of the obstacle in real time according to the relative distance, and if the mechanical arm of the robot enters the influence range, implementing an obstacle avoidance strategy; otherwise, the artificial potential field moves under the action of the gravitational potential field;
for a rapid obstacle, the obstacle avoidance method is characterized in that the obstacle avoidance method comprises the following steps: according to an artificial potential field method and the influence of a velocity potential field, the current resultant force direction of the mechanical arm is determined, position sampling is carried out in the reverse direction of the Z-axis component of the barrier velocity, and the position point with the highest evaluation function is selected as the position of the next moment.
2. The intelligent obstacle avoidance method for the mechanical arm facing the human-computer safe interaction as recited in claim 1, wherein the obstacle speed is calculated through the change of the obstacle position to obtain a speed influence factor for describing the obstacle motion state; or the robot monitors the identification code on the obstacle in real time through an identification code visual positioning method to obtain the position of the obstacle.
3. The intelligent obstacle avoidance method for the mechanical arm facing the human-computer safe interaction as claimed in claim 1, wherein the mechanical arm judges whether the obstacle is a fast obstacle or a slow or static obstacle according to the magnitude of the speed influence factor.
4. The intelligent obstacle avoidance method for the mechanical arm facing the human-computer safe interaction as claimed in claim 1, wherein the current resultant force of the mechanical arm specifically comprises:
Ftotal＝Fatt+Frep+Fvel
wherein, Fatt，Frep，FvelRespectively representing the attractive, repulsive and velocity repulsive forces experienced by the obstacle.
5. The intelligent obstacle avoidance method for the mechanical arm facing the human-computer safe interaction as recited in claim 3, wherein for the obstacle with slow moving speed or static moving speed, the obstacle is avoided in the positive direction of the obstacle speed or above the obstacle position point.
6. The intelligent obstacle avoidance method for the mechanical arm facing the human-computer safe interaction as recited in claim 1, wherein the adaptive step length setting is realized by increasing or decreasing the relative distance between the obstacle and the tail end of the mechanical arm of the robot and the change of the relative distance, specifically:
when the relative distance is reduced, based on the current relative distance and relative speed, and taking the influence radius of the dynamic obstacle as a reference, obtaining the longest time that the mechanical arm can move;
when the relative distance is smaller than or equal to the obstacle influence radius, sampling by adopting a fixed step length smaller than a set threshold value so as to reduce the collision probability;
when the relative distance is larger than the obstacle-influencing radius and the relative distance is increasing, the target point is directly selected as the next position point.
7. An intelligent mechanical arm obstacle avoidance system for man-machine safe interaction is characterized by comprising at least one robot with a mechanical arm and at least one obstacle with an identification code, wherein the robot avoids obstacles by using the intelligent mechanical arm obstacle avoidance method for man-machine safe interaction as claimed in any one of claims 1-6.
8. A robot for human-computer safe interaction is characterized in that the robot carries out obstacle avoidance by using the mechanical arm intelligent obstacle avoidance method for human-computer safe interaction as claimed in any one of claims 1 to 6.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010027287.2A CN111168681B (en) | 2020-01-10 | 2020-01-10 | Mechanical arm intelligent obstacle avoidance method and system for man-machine safety interaction and robot |
| LU102027A LU102027B1 (en) | 2020-01-10 | 2020-09-03 | Intelligent obstacle avoidance method and system of human-robot safe interaction oriented robotic arm |
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| CN202010027287.2A CN111168681B (en) | 2020-01-10 | 2020-01-10 | Mechanical arm intelligent obstacle avoidance method and system for man-machine safety interaction and robot |
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