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Sequential Manipulation Planning for Over-Actuated Unmanned Aerial Manipulators | IEEE Conference Publication | IEEE Xplore

Sequential Manipulation Planning for Over-Actuated Unmanned Aerial Manipulators


Abstract:

We investigate the sequential manipulation planning problem for unmanned aerial manipulators (UAMs). Unlike prior work that primarily focuses on one-step manipulation tas...Show More

Abstract:

We investigate the sequential manipulation planning problem for unmanned aerial manipulators (UAMs). Unlike prior work that primarily focuses on one-step manipulation tasks, sequential manipulations require coordinated motions of a UAM's floating base, the manipulator, and the object being manipulated, entailing a unified kinematics and dynamics model for motion planning under designated constraints. By leveraging a virtual kinematic chain (VKC)-based motion planning framework that consolidates components' kinematics into one chain, the sequential manipulation task of a UAM can be planned as a whole, yielding more coordinated motions. Integrating the kinematics and dynamics models with a hierarchical control framework, we demonstrate, for the first time, an over-actuated UAM achieves a series of new sequential manipulation capabilities in both simulation and experiment.
Date of Conference: 01-05 October 2023
Date Added to IEEE Xplore: 13 December 2023
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Conference Location: Detroit, MI, USA

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I. Introduction

Combining the agility of unmanned aerial vehicles (UAVs) and the flexibility of manipulators, UAMs can conduct manipulation tasks across rough terrains and in regions unreachable by ground robots [1]–[3]. Oftentimes, a fully-or even over-actuated UAV serves as the UAMs' flying vehicle [4]–[6]; this type of UAVs can track position and orientation independently to provide the UAM with more agile maneuver, achieve a larger reachable workspace, and obtain better dynamic properties compared with traditional multirotors. Existing UAMs leverage a bi-level schema by combining (i) a controller to stabilize the system and track the desired trajectory under forceful contacts with the environment and (ii) a motion planner to produce trajectories satisfying task-related constraints. Such a bi-level schema has succeeded in various aerial manipulation tasks, such as pick-and-place [3], [7], inspection [8], [9], valve operation [10], and door-like articulated object manipulation[11], [12].

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