Chen, Rui (Beihang University), Liu, Qianyuan (Beihang University), Chen, Zeshuai (Beihang University), Guo, Kexin (Beihang University), Yu, Xiang (Beihang University), Guo, Lei (Beihang University)

Online Trajectory Generation for Aerial Manipulator Subject to Multi-Tasks and Inequality Constraints

Scheduled for presentation during the Regular Session "Aerial Robotic Manipulation" (FrA1), Friday, June 9, 2023, 10:30−10:50, Room 118

2023 International Conference on Unmanned Aircraft Systems (ICUAS), June 6-9, 2023, Lazarski University, Warsaw, Poland

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

This article tackles the problem of generating coordinated trajectory for unmanned aerial manipulator (UAM) system. The kinematic redundancy nature of this class of system makes it challenging to design constraints-satisfied trajectories of both the aerial vehicle and the robotic arm simultaneously that can accomplish a series of tasks with varying levels of priority. This paper presents a redundancy utilized trajectory generation method based on hierarchical quadratic programming (HQP). The method is computationally inexpensive to execute online, allowing the UAM to dynamically adjust its configuration within inequality constraints (e.g. velocity bounds) to execute multi-tasks such as end-effector tracking, joint limits avoidance, and center of gravity (CoG) alignment. An experiment case study, where UAM is assigned to track and grasp a moving target, has been reported to illustrate the effectiveness of our approach.