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Bibliographic Details
Main Authors: Marticorena, Nicolas, Fischer, Tobias, Suenderhauf, Niko
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2512.09656
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author Marticorena, Nicolas
Fischer, Tobias
Suenderhauf, Niko
author_facet Marticorena, Nicolas
Fischer, Tobias
Suenderhauf, Niko
contents Reactive control can gracefully coordinate the motion of the base and the arm of a mobile manipulator. However, incorporating an accurate representation of the environment to avoid obstacles without involving costly planning remains a challenge. In this work, we present ReMoSPLAT, a reactive controller based on a quadratic program formulation for mobile manipulation that leverages a Gaussian Splat representation for collision avoidance. By integrating additional constraints and costs into the optimisation formulation, a mobile manipulator platform can reach its intended end effector pose while avoiding obstacles, even in cluttered scenes. We investigate the trade-offs of two methods for efficiently calculating robot-obstacle distances, comparing a purely geometric approach with a rasterisation-based approach. Our experiments in simulation on both synthetic and real-world scans demonstrate the feasibility of our method, showing that the proposed approach achieves performance comparable to controllers that rely on perfect ground-truth information.
format Preprint
id arxiv_https___arxiv_org_abs_2512_09656
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle ReMoSPLAT: Reactive Mobile Manipulation Control on a Gaussian Splat
Marticorena, Nicolas
Fischer, Tobias
Suenderhauf, Niko
Robotics
Reactive control can gracefully coordinate the motion of the base and the arm of a mobile manipulator. However, incorporating an accurate representation of the environment to avoid obstacles without involving costly planning remains a challenge. In this work, we present ReMoSPLAT, a reactive controller based on a quadratic program formulation for mobile manipulation that leverages a Gaussian Splat representation for collision avoidance. By integrating additional constraints and costs into the optimisation formulation, a mobile manipulator platform can reach its intended end effector pose while avoiding obstacles, even in cluttered scenes. We investigate the trade-offs of two methods for efficiently calculating robot-obstacle distances, comparing a purely geometric approach with a rasterisation-based approach. Our experiments in simulation on both synthetic and real-world scans demonstrate the feasibility of our method, showing that the proposed approach achieves performance comparable to controllers that rely on perfect ground-truth information.
title ReMoSPLAT: Reactive Mobile Manipulation Control on a Gaussian Splat
topic Robotics
url https://arxiv.org/abs/2512.09656