Research of path planning method for mobile robot based on artificial potential field

Ye, Binqiang; Zhao, Mingfu; Wang, Yi

doi:10.1109/icmt.2011.6003004

Cited by 15 publications

(10 citation statements)

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“…The reference steering angle was determined by using linear single-track vehicle model based on inverse dynamics method in following the desired path. The state-space represented the linear vehicle model equation can be expressed as below: (9) where, , , By using inverse method and negligible the effect of side slip angle, the steering angle value can be calculated as in equation (10). 10The desired steering angle was determined by considering the value of steering gear ratio and can be computed as follows: (11) For direct yaw moment control, the corrective yaw moment and corrective distributed torque both were formulated as equation (12) and (13) respectively based on works in [18,19].…”

Section: Control System Formulationmentioning

confidence: 99%

“…There are numerous motion planning techniques had been used in automotive vehicle navigation systems for collision avoidance. Motion planning using artificial potential field was introduced by [7] and had been implemented in robotics field [8,9] based on idea in filling the robot workspace with the information from environment. Application of potential field techniques in motion planning also had been extended into vehicle guidance systems including lane keeping [10] and obstacle avoidance [11].…”

Section: Introductionmentioning

confidence: 99%

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Potential Field Based Motion Planning with Steering Control and DYC for ADAS

et al. 2017

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In this study, the development of motion planning and control for collision avoidance driver assistance systems is presented. A potential field approach has been used in formulating the collision avoidance algorithm based on predicted vehicle motion. Then, to realize the advanced driver assistance systems (ADAS) for collision avoidance, steering control system and direct yaw moment control (DYC) is designed to follow the desired vehicle motion. Performance evaluation is conducted in simulation environment in term of its performance in avoiding the obstacles. Simulation results show that the vehicle collision avoidance assistance systems can successfully complete the avoidance behavior without colliding.

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Section: Control System Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Potential Field Based Motion Planning with Steering Control and DYC for ADAS

et al. 2017

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“…However , the traditional artificial potential field method has the limitations of local minimum and the target can not be reached. At present, there are many methods to jump out of the local minimum , such as increased guidance, introduced the escape force, geometric information method, simulated annealing algorithm, dynamic step length binary method, walking along the wall method and so on [2][3][4][5][6][7]. In this paper, the problem of local minimum is solved by changing the direction of repulsion force and the robot moves toward the target point.…”

Section: Introductionmentioning

confidence: 99%

Research of Robot Path Planning Based on Improved Artificial Potential Field

Du¹,

Nan²

2016

Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)

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Abstract. Though the artificial potential field applying to the path planning of mobile robot has the advantages of rapid respondent speed, small computation and real-time property, there are still problems such as the goal unreachable and existence of a local minimum point value, thus the improved artificial potential field is proposed in this paper. Considering the relative distance between the robot and the goal the improved algorithm adopts the improved potential function to make sure that the goal is the global minimum of the whole potential field. The repulsion direction is modified to avoid the robot suffers into local minimum, so the robot can reach the goal freely. The simulation results show that the robot can get a smooth and no touching optimal path in the environment of many obstacles. The effectiveness of the improved algorithm is verified.

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“…Robot motion planning has been studied for many years, and there are many different studies using different approaches for motion planning problems [1], such as A * [2], D * [3], artificial potential field [4], visibility graph [5] and methods based on optimal control problem [6].…”

Section: Introductionmentioning

confidence: 99%

Motion planning for non-holonomic mobile robots using the i-PID controller and potential field

Zheng²,

Perruquetti

et al. 2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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This paper proposes a motion planning approach for non-holonomic mobile robots. Firstly, motion planning using i-PID controller is presented. Then we improve the old potential field function to produce smooth repulsive force. Finally a new repulsive function of robot orientation and angular velocity is proposed to improve the performance of obstacle avoidance. The effectiveness and the robustness of the proposed method are shown thereafter via several simulations.

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Research of path planning method for mobile robot based on artificial potential field

Cited by 15 publications

References 0 publications

Potential Field Based Motion Planning with Steering Control and DYC for ADAS

Potential Field Based Motion Planning with Steering Control and DYC for ADAS

Research of Robot Path Planning Based on Improved Artificial Potential Field

Motion planning for non-holonomic mobile robots using the i-PID controller and potential field

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