Nonlinear Variable Structure Filter for the Online Trajectory Scaling

Abstract

Time efficiency and accurate path tracking represent two conflicting demands typical of robotic applications: Time efficiency induces one to plan extremely fast trajectories which can easily collide with the manipulator kinematic and dynamic constraints, thus causing a reduction of accuracy. To deal with this problem, several approaches can be found in the literature mainly based on the synthesis of dynamic filters used for the online trajectory scaling: A possibly unfeasible input trajectory is automatically scaled to fulfill given dynamic bounds. In this way, an accurate path tracking is guaranteed. This paper can be collocated in such a framework. A new discrete-time filter, with novel capabilities, is designed. Differently from other proposals, not only torque constraints are considered but also kinematic constraints are easily handled. Moreover, to preserve time efficiency, the new filter always attempts to recover any delay caused by the constraints.