Co-design and integration of vehicle navigation and control and state estimation is key for enabling field deployment of mobile robots in GPS-denied cluttered environments,and sensor calibration is critical for succes...Co-design and integration of vehicle navigation and control and state estimation is key for enabling field deployment of mobile robots in GPS-denied cluttered environments,and sensor calibration is critical for successful operation of both subsystems.This paper demonstrates the potential of this co-design approach with field tests of the integration of a reactive receding horizon-based motion planner and controller with an inertial aided multi-sensor calibration scheme.The reported method provides accurate calibration parameters that improve the performance of the state estimator,and enable the motion controller to generate smooth and continuous minimal-jerk trajectories based on local LiDAR data.Numerical simulations in Unity,and real-world experimental results from the field corroborate the claims of e±cacy for the reported autonomous navigation computational pipeline.展开更多
基金supported by U.S.Army Combat Capabilities Development Command——Army Research Lab via award#W911NF-20-2-0098.
文摘Co-design and integration of vehicle navigation and control and state estimation is key for enabling field deployment of mobile robots in GPS-denied cluttered environments,and sensor calibration is critical for successful operation of both subsystems.This paper demonstrates the potential of this co-design approach with field tests of the integration of a reactive receding horizon-based motion planner and controller with an inertial aided multi-sensor calibration scheme.The reported method provides accurate calibration parameters that improve the performance of the state estimator,and enable the motion controller to generate smooth and continuous minimal-jerk trajectories based on local LiDAR data.Numerical simulations in Unity,and real-world experimental results from the field corroborate the claims of e±cacy for the reported autonomous navigation computational pipeline.