Cost-Aware Kinematically Feasible Planning for Mobile and Surface Robotics¶
Authors: Steve Macenski, Matthew Booker, Joshua Wallace, Tobias Fischer
Published: 2026 (Journal Paper)
Source: IEEE Robotics and Automation Practice
Algorithm: Smac Planner
DOI: 10.1109/RAP.2026.3684018
Summary¶
Abstract¶
We present Smac Planner, an openly available, search based planning framework that addresses the critical need for kinematically feasible path planning across diverse robot plat forms. 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 and surface 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.