Kinodynamic Motion Planning for Collaborative Object Transportation by Multiple Mobile Manipulators
🤖 AI Summary
This paper addresses motion planning for cooperative transportation of objects by multiple mobile manipulators in dynamic environments. We propose a hierarchical collaborative planning framework: (1) narrow-corridor-enhanced global path planning generates safe topological paths; (2) receding-horizon optimization jointly plans trajectories for both mobile bases and manipulator arms within a unified convex conic state space, where dynamics constraints and self-collision avoidance are inherently embedded without auxiliary constraints; and (3) real-time avoidance of static and dynamic obstacles is achieved. The method synergistically integrates global path guidance with online trajectory replanning, ensuring kinematic and dynamic feasibility while meeting real-time computational requirements. Simulation and physical experiments demonstrate significant improvements in cooperative transport success rate and control energy efficiency. Trajectory generation latency remains below 50 ms, confirming strong robustness and practical engineering applicability.
Application Category
📝 Abstract
This work proposes a kinodynamic motion planning technique for collaborative object transportation by multiple mobile manipulator robots (MMRs) in dynamic environments. A global path planner computes a linear piece-wise path connecting the start to the goal. We proposed an algorithm that aids the path planner in defining the narrow regions between the static obstacles and enhances the feasibility of the global path. We formulate a novel online motion planning technique for the trajectory generations, minimizing the control efforts in a receding horizon manner. The motion planner plans the trajectory for finite time horizons considering the kinodynamic constraints and the static and dynamic obstacles. The motion planner jointly plans for the mobile bases and the arms to utilize the locomotion capability of the mobile base and the manipulation capability of the arm efficiently. We have introduced a convex cone approach to avoid self-collision of the formation by modifying the MMR's admissible state without imposing additional constraints. Numerical simulations and hardware experiments showcase the efficiency of the proposed approach.
Problem
Research questions and friction points this paper is trying to address.
Develops kinodynamic motion planning for multiple mobile manipulators in dynamic environments.
Enhances path feasibility by detecting narrow regions and defining obstacle-free areas.
Minimizes control efforts with local online trajectory planning considering kinodynamic constraints.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Global path planner computes linear piecewise path
Local online motion planning minimizes control efforts
Convex cone approach avoids self-collision without constraints
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