Efficient trajectory reshaping in a dynamic environment
2018 IEEE 15th International Workshop on Advanced Motion Control (AMC), 2018•ieeexplore.ieee.org
A general trajectory planner for optimal control problems is presented and applied to a robot
system. The approach is based on timed elastic bands and nonlinear model predictive
control. By exploiting the sparsity in the underlying optimization problems the computational
effort can be significantly reduced, resulting in a real-time capable planner. In addition, a
localization based switching strategy is employed to enforce convergence and stability. The
planning procedure is illustrated in a robotics application using a realistic SCARA type robot.
system. The approach is based on timed elastic bands and nonlinear model predictive
control. By exploiting the sparsity in the underlying optimization problems the computational
effort can be significantly reduced, resulting in a real-time capable planner. In addition, a
localization based switching strategy is employed to enforce convergence and stability. The
planning procedure is illustrated in a robotics application using a realistic SCARA type robot.
A general trajectory planner for optimal control problems is presented and applied to a robot system. The approach is based on timed elastic bands and nonlinear model predictive control. By exploiting the sparsity in the underlying optimization problems the computational effort can be significantly reduced, resulting in a real-time capable planner. In addition, a localization based switching strategy is employed to enforce convergence and stability. The planning procedure is illustrated in a robotics application using a realistic SCARA type robot.
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