Coupled Mobile Manipulation via Trajectory Optimization with Free Space Decomposition

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Abstract

This paper presents a real-time method for whole-body trajectory optimization of mobile manipulators in simplified dynamic and unstructured environments. Current trajectory optimization methods typically use decoupling of the mobile base and the robotic arm, which reduces flexibility in motion, does not scale to unstructured environments, and does not consider the future evolution of the environment, which is crucial to avoid dynamic obstacles. Given a goal configuration, such as waypoints generated by a global path planner, we formulate a receding horizon trajectory optimization minimizing the distance-to-target while avoiding collisions with static and dynamic obstacles. The presented method unifies the control of a robotic arm and a non-holonomic base to allow coupled trajectory planning. For collision avoidance, we propose to compute three convex regions englobing the robot's major body parts (i.e., base, shoulder-link and wrist-link) and thus reducing and limiting the number of inequality constraints, regardless of the number of obstacles in the environment. Moreover, our approach incorporates predicted trajectory information to smoothly, and in advance, avoid dynamic obstacles. The presented results show that trajectory optimization for the coupled system can reduce the total execution time by 48% and that applying the convex region generation for individual links allows keeping the computational costs low, even for complex scenarios, enabling onboard implementation.
Original languageEnglish
Title of host publicationProceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA)
PublisherIEEE
Pages12759-12765
ISBN (Electronic)978-1-7281-9077-8
ISBN (Print)978-1-7281-9078-5
DOIs
Publication statusPublished - 2021
EventICRA 2021: IEEE International Conference on Robotics and Automation - Hybrid at Xi'an, China
Duration: 30 May 20215 Jun 2021

Conference

ConferenceICRA 2021
Country/TerritoryChina
CityHybrid at Xi'an
Period30/05/215/06/21

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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