Time-Optimal Path Tracking for Jerk Controlled Robots

作者: Alessandro Palleschi , Manolo Garabini , Danilo Caporale , Lucia Pallottino

DOI: 10.1109/LRA.2019.2929979

关键词: RobotComputer scienceAccelerationTrajectoryRobot kinematicsActuatorControl theoryTorqueJerkOptimization problem

摘要: This letter presents a new approach to solve the time-optimal path tracking under limited joint range and bounds on velocity, acceleration, jerk. To obtain smooth continuous accelerations, with beneficial effects for load wear actuators but impact performance, we state minimum-time problem jerk as control input. The main contribution of this is formulation that includes constraints in optimization that, even if resulting non-linear programming non-convex, allows perform an efficient reliable convex relaxation using McCormick envelopes. Simulations experimental tests two 7-DoF manipulators have been carried out show benefits proposed compare it state-of-the-art techniques.

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