Safeguarding Learning-Based Planners Under Motion and Sensing Uncertainties Using Reachability Analysis
Akshay Shetty,Adam Dai,Alexandros Tzikas,Grace Gao,Akshay Shetty,Adam Dai,Alexandros Tzikas,Grace Gao
Learning-based trajectory planners in robotics have attracted growing interest given their ability to plan for complex tasks. These planners are typically trained in simulation under nominal conditions before being implemented on real robots. However, in real settings, the presence of motion and sensing uncertainties causes the robot to deviate from planned reference trajectories potentially leadi...
