Trajectory Optimization for Differential Drive Mobile Manipulators via Topological Paths Search and Arc Length-Yaw Parameterization
🤖 AI Summary
Addressing the challenge of generating collision-free, topologically diverse, and dynamically feasible trajectories for differentially driven mobile manipulators in complex environments, this paper proposes a hierarchical optimization framework. At the upper level, topology-aware path search generates multiple classes of collision-free candidate paths. At the lower level, a curvilinear abscissa–yaw angle parameterization explicitly encodes nonholonomic constraints, while polynomial trajectory representation combined with parallel sampling-based optimization efficiently yields smooth, globally optimal whole-body motion trajectories satisfying dynamic feasibility. The key contribution lies in the tight integration of topology-guided path search with a nonholonomic-preserving parameterization scheme, which simultaneously ensures trajectory feasibility and significantly improves planning success rate and trajectory quality. Experimental results demonstrate strong robustness and promising real-time capability in dynamic obstacle environments and narrow spaces.
Application Category
📝 Abstract
We present an efficient hierarchical motion planning pipeline for differential drive mobile manipulators. Our approach first searches for multiple collisionfree and topologically distinct paths for the mobile base to extract the space in which optimal solutions may exist. Further sampling and optimization are then conducted in parallel to explore feasible whole-body trajectories. For trajectory optimization, we employ polynomial trajectories and arc length-yaw parameterization, enabling efficient handling of the nonholonomic dynamics while ensuring optimality.
Problem
Research questions and friction points this paper is trying to address.
Efficient motion planning for differential drive mobile manipulators
Searching collision-free paths for mobile base optimization
Trajectory optimization using polynomial and arc length-yaw methods
Innovation
Methods, ideas, or system contributions that make the work stand out.
Hierarchical motion planning pipeline
Topologically distinct paths search
Arc length-yaw parameterization optimization
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