MobiDock: Design and Control of A Modular Self Reconfigurable Bimanual Mobile Manipulator via Robotic Docking

2025-10-31

AI Summary

Multi-robot collaborative manipulation faces challenges of high control complexity and poor dynamic stability. This paper proposes MobiDock—a modular, self-reconfigurable mobile manipulator system that physically docks autonomously to form a unified bimanual robotic platform, thereby reducing multi-robot coordination to single-system control. Its core innovation lies in a high-precision, high-rigidity autonomous docking mechanism integrating AprilTag-based visual guidance with a novel threaded locking mechanism. Experimental results demonstrate that, after docking, the system achieves a 32% reduction in RMS acceleration and jerk, a 41% improvement in end-effector angular positioning accuracy, and a 2.3× increase in task completion speed—significantly outperforming conventional distributed collaboration approaches. This work establishes a new reconfiguration paradigm for mobile manipulation robots, balancing robustness, precision, and operational efficiency.

Technology Category

• Intelligent Robots: Manipulation
• Multiagent Systems: Coordination and Collaboration
• Computer Vision: Multi-modal Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

Multi-robot systems, particularly mobile manipulators, face challenges in control coordination and dynamic stability when working together. To address this issue, this study proposes MobiDock, a modular self-reconfigurable mobile manipulator system that allows two independent robots to physically connect and form a unified mobile bimanual platform. This process helps transform a complex multi-robot control problem into the management of a simpler, single system. The system utilizes an autonomous docking strategy based on computer vision with AprilTag markers and a new threaded screw-lock mechanism. Experimental results show that the docked configuration demonstrates better performance in dynamic stability and operational efficiency compared to two independently cooperating robots. Specifically, the unified system has lower Root Mean Square (RMS) Acceleration and Jerk values, higher angular precision, and completes tasks significantly faster. These findings confirm that physical reconfiguration is a powerful design principle that simplifies cooperative control, improving stability and performance for complex tasks in real-world environments.

Problem

• Transforms multi-robot control into single system management
• Enhances dynamic stability and operational efficiency via docking
• Simplifies cooperative control through physical reconfiguration principle

Innovation

• Modular self-reconfigurable system via robotic docking
• Vision-based docking with AprilTag markers and screw-lock
• Transforms multi-robot control into unified single system