Safe Model Predictive Control of a Non-Holonomic Mobile Manipulator Under Multiple Constraints Using Control Barrier Functions

Safe Model Predictive Control of a Non-Holonomic Mobile Manipulator Under Multiple Constraints Using Control Barrier Functions

This paper introduces a novel control strategy to ensure safety in the navigation of a mobile manipulator comprising a fixed-base manipulator mounted on a mobile platform. The approach initially addresses the trajectory tracking problem of a non-holonomic mobile manipulator (NH-MM) by employing deco...

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Bibliographic Details
Main Authors: Zahra Kashi, Meysam Yadegar, Nader Meskin, Christos G. Cassandras
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Mobile manipulator
safety
obstacle avoidance
control barrier function (CBF)
model predictive control (MPC)
optimizable-CBF (OCBF)
Online Access:https://ieeexplore.ieee.org/document/10979937/
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Summary:This paper introduces a novel control strategy to ensure safety in the navigation of a mobile manipulator comprising a fixed-base manipulator mounted on a mobile platform. The approach initially addresses the trajectory tracking problem of a non-holonomic mobile manipulator (NH-MM) by employing decoupling dynamic control through model predictive control-optimizable control barrier function (MPC-OCBF). This allows for independent control of the end-effector and mobile platform trajectories, obstacle avoidance, and simultaneously adjusting the joint and control input limitations. The objective is to leverage the system’s redundancy to enable the mobile platform to effectively navigate feasible obstacle avoidance scenarios without affecting the primary task performance of the end-effector. Additionally, the method aims to perform obstacle avoidance when the redundancy of the manipulator is insufficient, addressing non-feasible obstacle avoidance scenarios. Through this approach, the mobile manipulator effectively avoids obstacles, allowing the end-effector to autonomously carry out its intended task. The effectiveness of the proposed method is validated through simulations and comparison with existing approaches. Additionally, a quantitative analysis is provided to evaluate and compare the performance of the controllers.
ISSN:2169-3536

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