Time-Optimal Handover Trajectory Planning for Aerial Manipulators based on Discrete Mechanics and Complementarity Constraints

TL;DR

This paper introduces a novel optimization framework combining discrete mechanics and complementarity constraints to plan time-optimal trajectories for aerial manipulators during parcel handovers, ensuring dynamic feasibility and automatic handover timing.

Contribution

It presents a new framework that integrates discrete variational mechanics and complementarity constraints for optimal trajectory planning in aerial manipulation tasks.

Findings

The framework reliably estimates system dynamics in simulations.

Automatic determination of handover opportunities based on constraints.

Successful validation through numerical simulations and hardware experiments.

Abstract

Planning a time-optimal trajectory for aerial robots is critical in many drone applications, such as rescue missions and package delivery, which have been widely researched in recent years. However, it still involves several challenges, particularly when it comes to incorporating special task requirements into the planning as well as the aerial robot's dynamics. In this work, we study a case where an aerial manipulator shall hand over a parcel from a moving mobile robot in a time-optimal manner. Rather than setting up the approach trajectory manually, which makes it difficult to determine the optimal total travel time to accomplish the desired task within dynamic limits, we propose an optimization framework, which combines discrete mechanics and complementarity constraints (DMCC) together. In the proposed framework, the system dynamics is constrained with the discrete variational Lagrangian mechanics that provides reliable estimation results also according to our experiments. The handover opportunities are automatically determined and arranged based on the desired complementarity constraints. Finally, the performance of the proposed framework is verified with numerical simulations and hardware experiments with our self-designed aerial manipulators.