CN113703448A - Ackerman chassis obstacle avoidance control method based on ultrasonic waves - Google Patents
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Abstract
The invention discloses an Ackerman chassis obstacle avoidance control method based on ultrasonic waves, which comprises the following steps: (1) installing a plurality of ultrasonic sensors on the Ackerman chassis and constructing a measurement model of the ultrasonic sensors; (2) modeling the steering lag of the Ackerman chassis to obtain a motion prediction model; (3) the ultrasonic sensor acquires ranging data in real time to obtain a point set coordinate of the barrier at the current moment; (4) calculating to obtain the pose of the Ackerman chassis under the coordinate system of the odometer at the current moment; (5) obtaining the pose of the ackerman chassis under the coordinate system of the odometer at the next moment and judging whether the ackerman chassis collides with the barrier; if collision occurs, controlling the Ackerman chassis to stop; if the collision does not occur, turning to the step (6); and (6) repeating the steps (3) to (5) until the prediction time threshold is reached. The invention can predict whether the Ackerman chassis is collided when moving, and avoid collision accidents caused by blind areas of visual field of operators.
Description
Technical Field
The invention relates to the field of mobile robot control, in particular to an Ackerman chassis obstacle avoidance control method based on ultrasonic waves.
Background
In recent years, the technology in the fields of robotics and autopilot has risen and has grown. In order to automate labor-intensive services such as construction, fire protection, and the like, many research institutes and companies transform engineering machinery vehicles into mobile robots, and attempt to apply robots and automatic driving techniques to related fields.
The engineering machinery vehicles sold in the market are mainly divided into a diesel engine drive mode and an electric drive mode according to power sources, wherein the diesel engine drive mode needs daily maintenance and is not suitable for being transformed into a mobile robot. The electric engineering mechanical vehicle can be roughly divided into two chassis types of a crawler type and an ackerman type, and generally, the crawler can damage the ground and is not suitable for paved road surfaces. Therefore, the electrically driven ackermann-type construction machine vehicle is very suitable for being transformed into a general mobile robot system.
The electrically-driven ackermann engineering vehicle is generally driven by a motor to drive a rear wheel, the speed control performance of the motor of an actuating mechanism is better, and the control method is mature and reliable. The steering system is usually driven by hydraulic pressure, the hydraulic control system is widely applied to various fields of engineering, particularly to the application with higher load requirement, and the hydraulic drive system has the characteristics of simplicity, reliability, mature technology and low cost, and is a preferred drive system of large-scale equipment. However, the hydraulically driven control system needs to deal with strong nonlinear system dynamic characteristics, and high requirements are put on position dynamic following control of the hydraulic system. In actual engineering practice, an operator often operates a hydraulic drive system through observation, for example, a mechanical arm of equipment such as an excavator and a crane is hydraulically driven, and the operator needs to repeatedly adjust the hydraulic drive system according to an observed position.
Limited by cost and technical maturity, manufacturers of engineering vehicles mostly adopt a switch type electromagnetic valve as an actuating mechanism of a hydraulic control system, and simulate a proportional type electromagnetic valve through PWM (pulse width modulation) to carry out open-loop control on the position of the hydraulic system (depend on observation of an operator to carry out feedback control). For vehicles with modification requirements, manufacturers usually add an absolute encoder to the front wheel steering position, and perform feedback control through position information fed back by the encoder. Due to the nonlinear influence of the hydraulic system, the control bandwidth of the whole control system is low, the response of the system is slow, and position adjustment is often required after the in-cylinder pressure is built. In addition, the switch type electromagnetic valve realizes pulse width modulation through fixed-period and quick switching, so that the position tracking performance of the hydraulic control system is further reduced.
In summary, large ackermann chassis systems are slow to respond. Meanwhile, with the rise of the automatic driving technology, after the ackerman chassis is transformed into a mobile robot, in the process of field deployment, the mobile robot needs to operate under the remote control of an operator, and a map for navigation and positioning is established for the surrounding environment based on a laser radar sensor. Due to the fact that the Ackermann chassis is large in size (the length of a vehicle body exceeds 4 meters) and loads are several tons, the problem that visual field blind areas exist when an operator conducts remote control exists, in addition, due to the fact that the hydraulic system lags behind, the response of the system is not timely, the blind areas can be collided with obstacles under the condition that protection is not conducted, and therefore personnel and equipment are seriously lost.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the defects, the invention provides an Ackerman chassis obstacle avoidance control method based on ultrasonic waves, which can predict whether the Ackerman chassis collides during movement and avoid the collision accident of operators caused by the blind zone of the visual field.
The technical scheme is as follows:
an Ackerman chassis obstacle avoidance control method based on ultrasonic waves comprises the following steps:
step (1), installing a plurality of ultrasonic sensors on an Ackerman chassis, and constructing a measurement model of the ultrasonic sensors;
modeling the steering delay of the ackerman chassis according to the kinematic model of the ackerman chassis to obtain a motion prediction model of the ackerman chassis;
step (3) the ultrasonic sensor acquires ranging data in real time, and point set coordinates measured by the ultrasonic sensor at the current moment are obtained according to the step (1) and are converted into a coordinate system of the odometer;
calculating the pose of the ackerman chassis at the current moment under a coordinate system of the odometer according to the pose of the ackerman chassis at the initial position and the odometer, and calculating the pose of the ackerman chassis at the next moment under the coordinate system of the odometer according to the step (2);
step (5), whether the Ackerman chassis collides with the barrier at the next moment is judged by combining the step (3) and the step (4); if collision occurs, controlling the Ackerman chassis to stop; if the collision does not occur, turning to the step (6);
and (6) repeating the steps (3) to (5) until the prediction time threshold is reached.
The measurement model of the ultrasonic sensor constructed in the step (1) is as follows:
Lithe method comprises the steps that a point set of measurement results of the ith ultrasonic sensor is represented, i belongs to {1, 2.. multidot., n }, and n represents the number of the ultrasonic sensors; suppose that the return value of the range measurement of the ith ultrasonic sensor is diThen L isiThe coordinate set calculation method under the corresponding ultrasonic sensor coordinate system is as follows:
wherein, sonar (i) represents a coordinate system of the ith ultrasonic sensor, and the coordinate system is established by taking the position of the ultrasonic sensor as an origin; (x, y) each represents LiCoordinate of a certain point in the coordinate system of the corresponding ultrasonic sensor, thetaiIndicates the field angle of the ith ultrasonic sensor,
represents the maximum measurement distance range of the i-th ultrasonic sensor.
In the step (1), the number N of the ultrasonic sensors is equal to the coverage area/FOV, where FOV represents the range detected by the ultrasonic sensors.
The coverage range is 360 degrees, and the detection distance of the ultrasonic sensor is 2-3 meters away from the edge position of the ackermann chassis in the circumferential direction of the ackermann chassis.
The step (2) is specifically as follows:
adopting a first-order system to represent a steering control hysteresis result of a steering system;
wherein, TsteerThe method comprises the steps of representing a first-order approximate system time constant of a steering system, recording different input and output data measurement through experiments, and obtaining the time constant through a least square method; δ represents the steering angle signal received by the steering wheel, δactualRepresenting the current steering angle obtained by the sensor measurement;
suppose that the remote control forward speed and steering angle signals received by the current controller are v respectivelyxAnd δ, the kinematic model of the ackermann chassis in the odometer coordinate system is as follows:
wherein L iswbRepresenting the distance from the front wheel to the rear wheel of the ackerman chassis;
the above model is denoted as state X of ackermann chassis, from which:
and further obtaining a motion prediction model of the Ackerman chassis:
Xk+1＝H(Xk,uk,dt)
wherein dt is the step time of the forward predicted motion; xkRepresents the state of the ackerman chassis at the k-th moment, ukRepresenting the remote control command signal received by the ackerman chassis at time k.
The step (3) of transforming the coordinates of the point set measured by the ultrasonic sensor at the current moment into the coordinate system of the odometer specifically comprises the following steps:
and converting the coordinates of the corresponding point set into a robot coordinate system according to the installation parameters of the ultrasonic sensor to obtain:
baseL＝baseTsonar(i)⊙sonar(i)L(di,θi)
wherein the content of the first and second substances,basel represents a point set coordinate measured by the ultrasonic sensor under a robot coordinate system;baseTsonar(i)a homogeneous transformation matrix representing the robot coordinate system to the ith ultrasonic sensor; an operator indicates a dot product operation for performing dot product on each dot in the homogeneous transformation matrix and the dot set coordinates;
the transformation relation between the coordinate system of the odometer at the current moment and the coordinate system of the robot is obtained through the calculation of the odometerodomTbaseAnd projecting the coordinates of the point set obtained by the current ultrasonic sensor measurement to the coordinate system of the odometer to obtain:
odomL＝odomTbase⊙baseL＝odomTbase baseTsonar(i)⊙sonar(i)L(di,θi)
wherein the content of the first and second substances,odoml is expressed in the coordinate system of the odometerAnd point set coordinates measured by the ultrasonic sensor at the previous moment.
The pose of the Ackerman chassis at the next moment under the coordinate system of the odometer is calculated in the step (4) as follows:
calculating the pose of the ackerman chassis at the moment k in the coordinate system of the odometer according to the pose of the ackerman chassis at the initial position in the coordinate system of the odometer and the odometerodomP(k)＝[xk,yk,θk]And (3) calculating according to the step (2) to obtain the pose of the Ackerman chassis at the next moment under the coordinate system of the odometer as follows:
odomP(k+1)＝Xk+1＝H(Xk,uk,dt)
calculating to obtain a homogeneous transformation matrix from the coordinate system of the odometer to the coordinate system of the robot at the moment k +1odomTbase(k +1), then the coordinate set of the shape of the ackermann chassis at time k +1 in the odometer coordinate system is as follows:
odomFABCD＝odomTbase(k+1)⊙baseFABCD
wherein the content of the first and second substances,baseFABCDa set of coordinates representing the shape of the ackermann chassis wheel in the robot coordinate system.
The step (5) of judging whether the ackermann chassis collides with the obstacle at the next moment specifically comprises the following steps:
coordinate set of the shape of the ackerman chassis at the moment k +1 in the coordinate system of the odometerodomFABCDCombining the point set coordinate obtained by the step (3) and measured by the ultrasonic sensor at the current moment in the coordinate system of the odometerodomL, if satisfied
The pose of the Ackerman chassis shape at the moment of k +1 predicted at present under the coordinate system of the odometer and the obstacle do not collide; otherwise a collision is considered to occur.
And (5) predicting whether future motion of the Ackerman chassis is collided or not according to the steps (5) and (6), and planning motion according to a prediction result.
Has the advantages that:
1. when the large ackerman chassis remote control mapping is deployed, whether the ackerman chassis collides during movement can be predicted, and collision accidents caused by visual field blind areas of operators are avoided.
2. The invention can be started when the mobile robot moves at a low speed, and is used as a supplementary protection measure for navigation obstacle avoidance.
3. The invention has universality and theoretically supports the layout of various ultrasonic sensors.
4. The invention comprehensively considers the lag of the hydraulic system and has more accurate prediction and judgment on the track.
Drawings
Fig. 1 is a schematic diagram of the ackermann chassis remote control of the present invention.
Fig. 2 is a flow chart of the ackerman chassis remote control method of the present invention.
Fig. 3 is a schematic diagram of the ackermann chassis remote control principle of the present invention.
FIG. 4 is a diagram of a measurement model of the ultrasonic sensor according to the present invention.
Detailed Description
The invention is further elucidated with reference to the drawings and the embodiments.
Fig. 1 is a schematic diagram of the ackermann chassis remote control of the present invention. As shown in figure 1, the conventional Ackermann chassis structure needs to be modified, and according to an application scene and actual requirements, a proper number of ultrasonic sensors are installed at intervals in the circumferential direction of the Ackermann chassis, and the detection distance of the ultrasonic sensors is 2-3 meters from the edge position of the Ackermann chassis in the circumferential direction of the Ackermann chassis.
In the invention, the number of specific ultrasonic sensors is determined according to actual requirements, and the general number N is the coverage area/FOV, wherein the FOV represents the range detected by the ultrasonic sensors; the coverage in the present invention is 360 °.
Fig. 2 is a flow chart of the ackerman chassis remote control method of the present invention. As shown in fig. 2, the ackermann chassis obstacle avoidance control method based on ultrasonic waves of the present invention includes the following steps:
(1) constructing a measurement model of the ultrasonic sensor;
fig. 3 is a schematic diagram of the ackermann chassis remote control principle of the present invention. As shown in FIG. 3, wherein LiThe method comprises the steps that a point set of measurement results of the ith ultrasonic sensor is represented, i belongs to {1, 2.. multidot., n }, and n represents the number of the ultrasonic sensors; suppose that the return value of the range measurement of the ith ultrasonic sensor is diThen L isiThe coordinate set calculation method under the corresponding ultrasonic sensor coordinate system is as follows:
wherein, sonar (i) represents a coordinate system of the ith ultrasonic sensor, and the coordinate system is established by taking the position of the ultrasonic sensor as an origin; (x, y) each represents LiCoordinate of a certain point in the coordinate system of the corresponding ultrasonic sensor, thetaiIndicates the field angle of the ith ultrasonic sensor,
represents the maximum measuring distance range of the ith ultrasonic sensor;
(2) modeling the steering lag of the ackerman chassis to obtain a motion prediction model of the ackerman chassis:
here, a first order system is used to approximate the steering control hysteresis result of the steering system;
wherein, TsteerThe first-order approximate system time constant of the steering system is represented, different input and output data measurement can be recorded through experiments, and then the first-order approximate system time constant is obtained through a least square method; δ represents the steering angle signal received by the steering wheel, δactualRepresenting the current steering angle obtained by the sensor measurement;
considering the motion situation of Ackerman chassis, suppose the remote received by the current controllerSignals for controlling forward speed and steering angle are respectively vxAnd δ, the kinematic model of the complete ackermann chassis in the odometer coordinate system is as follows:
wherein L iswbRepresenting the distance from the front wheel to the rear wheel of the ackerman chassis;
the above system of differential equations in continuous time can be simplified as:
discretizing the vector to obtain:
Xk+1＝H(Xk,uk,dt)
wherein dt is the step time of the forward predicted motion; xkRepresents the state of the ackermann chassis at time k (including coordinates, orientation, and steering lag results), ukThe remote controller command signal received by the ackerman chassis at the moment k is represented;
(3) the ultrasonic sensor acquires ranging data in real time, obtains a coordinate set of a point set measured by the ultrasonic sensor at the current moment according to the step (1), and converts the corresponding coordinate set into a robot coordinate system according to installation parameters of the ultrasonic sensor to obtain:
baseL＝baseTsonar(i)⊙sonar(i)L(di,θi)
wherein the content of the first and second substances,basel represents a coordinate set of points measured by the ultrasonic sensor in a robot coordinate system;baseTsonar(i)a homogeneous transformation matrix representing the robot coordinate system to the ith ultrasonic sensor; an operator indicates a dot product operation for performing dot product on each dot in the homogeneous transformation matrix and the coordinate set;
(4) the transformation relation between the coordinate system of the odometer at the current moment and the coordinate system of the robot is obtained through the calculation of the odometerodomTbaseAnd projecting the coordinate set of the point set obtained by the current ultrasonic sensor measurement to the coordinate system of the odometer to obtain:
odomL＝odomTbase⊙baseL＝odomTbase baseTsonar(i)⊙sonar(i)L(di,θi)
wherein the content of the first and second substances,odoml represents a coordinate set of a point set measured by the ultrasonic sensor at the current moment in the coordinate system of the odometer;
(5) calculating the pose of the ackerman chassis at the moment k in the coordinate system of the odometer according to the pose of the ackerman chassis at the initial position in the coordinate system of the odometer and the odometerodomP(k)＝[xk,yk,θk]And (3) calculating according to the step (2) to obtain the pose of the Ackerman chassis at the next moment under the coordinate system of the odometer as follows:
odomP(k+1)＝Xk+1＝H(Xk,uk,dt)
calculating to obtain a homogeneous transformation matrix from the coordinate system of the odometer to the coordinate system of the robot at the moment k +1odomTbase(k +1), then the set of coordinates of the shape of the ackermann chassis in the odometer coordinate system at the next time is as follows:
odomFABCD＝odomTbase(k+1)⊙baseFABCD
wherein the content of the first and second substances,baseFABCDrepresenting a coordinate set of the Ackerman chassis wheel shape under a robot coordinate system;
(6) coordinate set of Ackerman chassis shape under odometer coordinate system according to k +1 momentodomFABCDCombining the coordinate set of the point set obtained by the step (3) and measured by the ultrasonic sensor at the current moment in the coordinate system of the odometerodomL, if satisfied
The Ackerman chassis pose at the k +1 moment predicted at present does not collide with the obstacle;
(7) repeating the steps (3) to (6) until the predicted total time TpredictIf collision between the obstacle and the robot is detected in the period, immediately controlling the Ackerman chassis to suddenly stop; furthermore, the invention can predict whether a collision happens at a future moment and can decelerate in advance until the collision stops according to actual conditions and needs.
Although the preferred embodiments of the present invention have been described in detail, the present invention is not limited to the details of the foregoing embodiments, and various equivalent changes (such as number, shape, position, etc.) may be made to the technical solution of the present invention within the technical spirit of the present invention, and these equivalent changes are all within the protection scope of the present invention.
Claims (9)
1. An Ackerman chassis obstacle avoidance control method based on ultrasonic waves is characterized by comprising the following steps: the method comprises the following steps:
step (1), installing a plurality of ultrasonic sensors on an Ackerman chassis, and constructing a measurement model of the ultrasonic sensors;
modeling the steering delay of the ackerman chassis according to the kinematic model of the ackerman chassis to obtain a motion prediction model of the ackerman chassis;
step (3) the ultrasonic sensor acquires ranging data in real time, obtains a point set coordinate of the obstacle measured by the ultrasonic sensor at the current moment according to the step (1), and transforms the point set coordinate to a coordinate system of the odometer;
calculating the pose of the ackerman chassis at the current moment under a coordinate system of the odometer according to the pose of the ackerman chassis at the initial position and the odometer, and calculating the pose of the ackerman chassis at the next moment under the coordinate system of the odometer according to the step (2);
step (5), whether the Ackerman chassis collides with the barrier at the next moment is judged by combining the step (3) and the step (4); if collision occurs, controlling the Ackerman chassis to stop; if the collision does not occur, turning to the step (6);
and (6) repeating the steps (3) to (5) until the prediction time threshold is reached.
2. The ackermann chassis obstacle avoidance control method according to claim 1, wherein: the measurement model of the ultrasonic sensor constructed in the step (1) is as follows:
Lithe method comprises the steps that a point set of measurement results of the ith ultrasonic sensor is represented, i belongs to {1, 2.. multidot., n }, and n represents the number of the ultrasonic sensors; suppose that the return value of the range measurement of the ith ultrasonic sensor is diThen L isiThe coordinate set calculation method under the corresponding ultrasonic sensor coordinate system is as follows:
wherein, sonar (i) represents a coordinate system of the ith ultrasonic sensor, and the coordinate system is established by taking the position of the ultrasonic sensor as an origin; (x, y) each represents LiCoordinate of a certain point in the coordinate system of the corresponding ultrasonic sensor, thetaiIndicates the field angle of the ith ultrasonic sensor,
represents the maximum measurement distance range of the i-th ultrasonic sensor.
3. The ackermann chassis obstacle avoidance control method according to claim 1, wherein: in the step (1), the number N of the ultrasonic sensors is equal to the coverage area/FOV, where FOV represents the range detected by the ultrasonic sensors.
4. The ackermann chassis obstacle avoidance control method according to claim 3, wherein: the coverage range is 360 degrees, and the detection distance of the ultrasonic sensor is 2-3 meters away from the edge position of the ackermann chassis in the circumferential direction of the ackermann chassis.
5. The ackermann chassis obstacle avoidance control method according to claim 1, wherein: the step (2) is specifically as follows:
adopting a first-order system to represent a steering control hysteresis result of a steering system;
wherein, TsteerThe method comprises the steps of representing a first-order approximate system time constant of a steering system, recording different input and output data measurement through experiments, and obtaining the time constant through a least square method; δ represents the steering angle signal received by the steering wheel, δactualRepresenting the current steering angle obtained by the sensor measurement;
suppose that the remote control forward speed and steering angle signals received by the current controller are v respectivelyxAnd δ, the kinematic model of the ackermann chassis in the odometer coordinate system is as follows:
wherein L iswbRepresenting the distance from the front wheel to the rear wheel of the ackerman chassis;
the above model is denoted as state X of ackermann chassis, from which:
and further obtaining a motion prediction model of the Ackerman chassis:
Xk+1＝H(Xk,uk,dt)
wherein dt is the step time of the forward predicted motion; xkRepresents the state of the ackerman chassis at the k-th moment, ukRepresenting the remote control command signal received by the ackerman chassis at time k.
6. The ackermann chassis obstacle avoidance control method according to claim 1, wherein: the step (3) of transforming the coordinates of the point set measured by the ultrasonic sensor at the current moment into the coordinate system of the odometer specifically comprises the following steps:
and converting the coordinates of the corresponding point set into a robot coordinate system according to the installation parameters of the ultrasonic sensor to obtain:
baseL＝baseTsonar(i)⊙sonar(i)L(di,θi)
wherein the content of the first and second substances,basel represents a point set coordinate measured by the ultrasonic sensor under a robot coordinate system;baseTsonar(i)a homogeneous transformation matrix representing the robot coordinate system to the ith ultrasonic sensor; an operator indicates a dot product operation for performing dot product on each dot in the homogeneous transformation matrix and the dot set coordinates;
calculated by odometerTransformation relation between coordinate system of odometer and coordinate system of robot at current momentodomTbaseAnd projecting the coordinates of the point set obtained by the current ultrasonic sensor measurement to the coordinate system of the odometer to obtain:
odomL＝odomTbase⊙baseL＝odomTbase baseTsonar(i)⊙sonar(i)L(di,θi)
wherein the content of the first and second substances,odomand L represents the coordinates of the point set measured by the ultrasonic sensor at the current moment in the coordinate system of the odometer.
7. The ackermann chassis obstacle avoidance control method according to claim 1, wherein: the pose of the Ackerman chassis at the next moment under the coordinate system of the odometer is calculated in the step (4) as follows:
calculating the pose of the ackerman chassis at the moment k in the coordinate system of the odometer according to the pose of the ackerman chassis at the initial position in the coordinate system of the odometer and the odometerodomP(k)＝[xk,yk,θk]And (3) calculating according to the step (2) to obtain the pose of the Ackerman chassis at the next moment under the coordinate system of the odometer as follows:
odomP(k+1)＝Xk+1＝H(Xk,uk,dt)
calculating to obtain a homogeneous transformation matrix from the coordinate system of the odometer to the coordinate system of the robot at the moment k +1odomTbase(k +1), then the coordinate set of the shape of the ackermann chassis at time k +1 in the odometer coordinate system is as follows:
odomFABCD＝odomTbase(k+1)⊙baseFABCD
wherein the content of the first and second substances,baseFABCDa set of coordinates representing the shape of the ackermann chassis wheel in the robot coordinate system.
8. The ackermann chassis obstacle avoidance control method according to claim 7, wherein: the step (5) of judging whether the ackermann chassis collides with the obstacle at the next moment specifically comprises the following steps:
coordinate set of the shape of the ackerman chassis at the moment k +1 in the coordinate system of the odometerodomFABCDCombining the point set coordinate obtained by the step (3) and measured by the ultrasonic sensor at the current moment in the coordinate system of the odometerodomL, if satisfied
The pose of the Ackerman chassis shape at the moment of k +1 predicted at present under the coordinate system of the odometer and the obstacle do not collide; otherwise a collision is considered to occur.
9. The ackermann chassis obstacle avoidance control method according to claim 1, wherein: and (5) predicting whether future motion of the Ackerman chassis is collided or not according to the steps (5) and (6), and planning motion according to a prediction result.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104503451A (en) * | 2014-11-27 | 2015-04-08 | 华南农业大学 | Obstacle-avoidance automatic guidance method and automatic guided vehicle based on vision and ultrasonic sensing |
| DE102018105014A1 (en) * | 2017-03-06 | 2018-09-06 | GM Global Technology Operations LLC | FORECAST ALGORITHM FOR A VEHICLE CRASH USING A RADAR SENSOR AND A UPA SENSOR |
| US20180251092A1 (en) * | 2017-03-06 | 2018-09-06 | GM Global Technology Operations LLC | Vehicle collision prediction algorithm using radar sensor and upa sensor |
| CN110703763A (en) * | 2019-11-05 | 2020-01-17 | 武汉理工大学 | Unmanned vehicle path tracking and obstacle avoidance method |
| CN111596666A (en) * | 2020-06-01 | 2020-08-28 | 上海运晓机器人有限公司 | Detection method for obstacle collision threat based on AGV motion prediction |
| CN112097792A (en) * | 2020-08-28 | 2020-12-18 | 上海大学 | Ackerman model mobile robot odometer calibration method |
| CN112506199A (en) * | 2020-12-12 | 2021-03-16 | 江西洪都航空工业集团有限责任公司 | Local path planning method based on dynamic window method and suitable for Ackerman model robot |
-
2021
- 2021-08-19 CN CN202110952853.5A patent/CN113703448A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104503451A (en) * | 2014-11-27 | 2015-04-08 | 华南农业大学 | Obstacle-avoidance automatic guidance method and automatic guided vehicle based on vision and ultrasonic sensing |
| DE102018105014A1 (en) * | 2017-03-06 | 2018-09-06 | GM Global Technology Operations LLC | FORECAST ALGORITHM FOR A VEHICLE CRASH USING A RADAR SENSOR AND A UPA SENSOR |
| US20180251092A1 (en) * | 2017-03-06 | 2018-09-06 | GM Global Technology Operations LLC | Vehicle collision prediction algorithm using radar sensor and upa sensor |
| CN110703763A (en) * | 2019-11-05 | 2020-01-17 | 武汉理工大学 | Unmanned vehicle path tracking and obstacle avoidance method |
| CN111596666A (en) * | 2020-06-01 | 2020-08-28 | 上海运晓机器人有限公司 | Detection method for obstacle collision threat based on AGV motion prediction |
| CN112097792A (en) * | 2020-08-28 | 2020-12-18 | 上海大学 | Ackerman model mobile robot odometer calibration method |
| CN112506199A (en) * | 2020-12-12 | 2021-03-16 | 江西洪都航空工业集团有限责任公司 | Local path planning method based on dynamic window method and suitable for Ackerman model robot |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023197668A1 (en) * | 2022-04-11 | 2023-10-19 | 北京京东乾石科技有限公司 | Obstacle avoidance control method and apparatus for robot |
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