Motion Control and Trajectory Planning for Obstacle Avoidance of the Mobile Parallel Robot Driven by Three Tracked Vehicles
Shuzhan Shentu, Fugui Xie, Xin-Jun Liu, Zhao Gong
Abstract
SUMMARY This paper proposes a mobile parallel robot (MPR) and focuses on obstacle avoidance. When analyzing the collision-free trajectories, the coupling constraints caused by the parallel mechanism and the obstacle should be emphatically solved. The solution is to divide the problem into two steps. First, the genetic algorithm is employed to search and optimize the feasible trajectories under the mechanism constraint of the MPR. Then the trajectory tracking controller is designed to make the tracked vehicles move cooperatively and track a trajectory asymptotically. Finally, simulations and experiments are carried out to verify the effectiveness of the solution.
Topics & Concepts
Obstacle avoidanceObstacleTrajectoryMobile robotComputer scienceMechanism (biology)Control theory (sociology)Constraint (computer-aided design)Collision avoidanceController (irrigation)RobotTracking (education)Motion (physics)Genetic algorithmMotion controlCollisionMotion planningControl engineeringArtificial intelligenceControl (management)EngineeringAgronomyBiologyMechanical engineeringAstronomyEpistemologyPhilosophyPolitical scienceLawComputer securityPsychologyPhysicsPedagogyMachine learningControl and Dynamics of Mobile RobotsRobotic Path Planning AlgorithmsRobotic Mechanisms and Dynamics