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.
View on arXiv@article{macenski2025_2401.13078,
title={ Open-Source, Cost-Aware Kinematically Feasible Planning for Mobile and Surface Robotics },
author={ Steve Macenski and Matthew Booker and Joshua Wallace and Tobias Fischer },
journal={arXiv preprint arXiv:2401.13078},
year={ 2025 }
}