Distributed Motion Control of Multiple Mobile Manipulator System with Disturbance and Communication Delay

In real-world object manipulation scenarios, multiple mobile manipulator systems may suffer from disturbances and asynchrony, leading to excessive interaction forces and causing object damage or emergency stops. This paper presents a novel distributed motion control approach aimed at reducing these unnecessary interaction forces. The control strategy only utilizes force information without the need for global position and velocity information. Disturbances are corrected through compensatory movements of the manipulators. Besides, the asymmetric, non-uniform, and time-varying communication delays between robots are also considered. The stability of the control law is rigorously proven by the Lyapunov theorem. Subsequently, the efficacy of the proposed control law is validated through simulations and experiments of collaborative object transportation by two robots. Experimental results demonstrate the effectiveness of the proposed control law in reducing interaction forces during object manipulation.

Motion Planning for Multiple Mobile Manipulator System in Complex Flipping Manipulation

Multiple robot systems are favored for object manipulation and transportation, especially for large objects. However, in more complex manipulation such as flipping, these systems encounter a new challenge, configuration disconnectivity of manipulators. Grasping objects by manipulators will impose closed-chain constraints on the system, which in turn limits the feasible motions of manipulators and further compromises the configuration connectivity. Multiple mobile manipulator systems show much more flexibility in object manipulation with the mobility of the mobile platform and have the potential to address the above problem. In this paper, a novel planning framework is proposed for complex flipping manipulation by incorporating platform motions and regrasping. Firstly, two types of trajectories, mobile manipulator planning and regrasping planning, are classified and can be assigned different priorities for different tasks. Secondly, corresponding planning methods are designed for each type of trajectory. Specifically, in mobile manipulator planning, the configuration of the platform is determined through optimization to ensure connectivity when the manipulator approaches configuration boundaries. In regrasping planning, closed-chain constraints are temporarily disregarded and the manipulation capabilities are prioritized to facilitate subsequent planning. Finally, the structure of the overall planning framework is provided. Experimental results demonstrate that the proposed planner efficiently plans the motions of the system to accomplish flipping manipulation. Additionally, a comprehensive experiment emphasizes the significance of our planner in extending the capabilities of multiple mobile manipulator systems in complex tasks.