日本フィジカルAI新聞

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arXiv:2401.13078

Open-Source, Cost-Aware Kinematically Feasible Planning for Mobile and Surface Robotics

Open-Source, Cost-Aware Kinematically Feasible Planning for Mobile and Surface Robotics

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著者: Steve Macenski, Matthew Booker, Joshua Wallace, Tobias Fischer

分類: cs.RO

原文アブストラクト

We present Smac Planner, an openly available, search-based planning framework that addresses the critical need for kinematically feasible path planning across diverse robot platforms. Smac Planner provides high-performance implementations of Cost-Aware A*, Hybrid-A*, and State Lattice planners that can be deployed for Ackermann, legged, and other large non-circular robots. Our framework introduces novel "Cost-Aware" variations that significantly improve performance in complex environments common to mobile robotics while maintaining kinematic feasibility constraints. Integrated as the standard planning system within the popular ROS 2 Navigation stack, Nav2, Smac Planner now powers thousands of robots worldwide across academic research, commercial applications, and field deployments.