TY - GEN
T1 - OC3
T2 - 19th IEEE International Conference on Automation Science and Engineering, CASE 2023
AU - Sinha, Anirban
AU - Laha, Riddhiman
AU - Chakraborty, Nilanjan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper presents a novel real-time motion planning method for differential drive mobile robots. Reactive planners, in the context of mobile robots, are usually vulnerable to challenges like local minima, differential constraint satisfaction, and dynamic obstacles. To this end, we present the Off-Center point Complementarity Constraint (OC3) planner, which respects the differential constraints of robot kinematics, can handle dynamic obstacles, and is more robust to the local minima problem compared to traditional methods like artificial potential fields. Our OC3 planner utilizes a virtual contact mechanism at a distal off-center point of the robot for obstacle avoidance, thereby ensuring smooth maneuvers. We formulate the obstacle avoidance problem as a feasibility problem with complementarity constraints, and derive a closed-form solution. This enables fast online computation of collision-free waypoints for the robot off-center. Once a collision-free state of the off-center point is found, inverse velocity kinematics is used to compute the reference control input velocities (? R2) for the robot. We further show that OC3 can be used as a local planner in RRT type of sampling-based global planning framework to avoid the local minimum problem. Our extensive analysis through various case studies and rigorous simulation experiments, using the popular ROS based Turtlebot3 simulator, in the presence of static and dynamic obstacles, demonstrate the efficacy of our framework including real-time proficiency.
AB - This paper presents a novel real-time motion planning method for differential drive mobile robots. Reactive planners, in the context of mobile robots, are usually vulnerable to challenges like local minima, differential constraint satisfaction, and dynamic obstacles. To this end, we present the Off-Center point Complementarity Constraint (OC3) planner, which respects the differential constraints of robot kinematics, can handle dynamic obstacles, and is more robust to the local minima problem compared to traditional methods like artificial potential fields. Our OC3 planner utilizes a virtual contact mechanism at a distal off-center point of the robot for obstacle avoidance, thereby ensuring smooth maneuvers. We formulate the obstacle avoidance problem as a feasibility problem with complementarity constraints, and derive a closed-form solution. This enables fast online computation of collision-free waypoints for the robot off-center. Once a collision-free state of the off-center point is found, inverse velocity kinematics is used to compute the reference control input velocities (? R2) for the robot. We further show that OC3 can be used as a local planner in RRT type of sampling-based global planning framework to avoid the local minimum problem. Our extensive analysis through various case studies and rigorous simulation experiments, using the popular ROS based Turtlebot3 simulator, in the presence of static and dynamic obstacles, demonstrate the efficacy of our framework including real-time proficiency.
UR - http://www.scopus.com/inward/record.url?scp=85174417558&partnerID=8YFLogxK
U2 - 10.1109/CASE56687.2023.10260592
DO - 10.1109/CASE56687.2023.10260592
M3 - Conference contribution
AN - SCOPUS:85174417558
T3 - IEEE International Conference on Automation Science and Engineering
BT - 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
PB - IEEE Computer Society
Y2 - 26 August 2023 through 30 August 2023
ER -