Stability-Aware Banked Turn Maneuver Control and Command Augmentation for 2-DOF Pendulum-Driven Spherical Robots
Derek Pravecek, Rishi Jangale, Aaron Villanueva, Robert Ambrose
AI summary
Problem
Executing banked turns at high speeds creates severe centripetal loading that limits feasible roll angles and overwhelms traditional low-speed steering models, leaving a gap in dynamic-aware autonomy for spherical robots.
Approach
The authors derive a closed-form steady-state torque model to quantify speed-dependent steering limits, then integrate these constraints into a real-time Command Augmentation System that automatically scales down infeasible roll commands based on velocity and internal pressure.
Key results
- Closed-form steady-state pendulum angle expression for banked turns
- Centripetal and centrifugal torques dominate steering dynamics above 3 rad/s
- Velocity-dependent maximum roll angle limit function to prevent collisions
- Experimental validation of stable banked turns up to 6 rad/s on RoboBall II
Why it matters
This work enables safer, higher-speed maneuvering for soft-shell spherical robots in exploration and rescue applications by preventing dynamic instability and mechanical collisions during aggressive turns.
Abstract
Executing banked turns at elevated speeds poses significant dynamic challenges for 2-DOF pendulum-driven spherical robots. A steady-state torque balance reveals that centripetal loading at high speeds limits feasible roll angles and demands increasingly aggressive pendulum actuation. We derive a closed-form expression for the required pendulum angle and integrate this into a bank-aware Command Aug- mentation System (CAS) and control law that automatically alters infeasible commands. Experimental tests on Texas A&M RAD Lab’s RoboBall II platform demonstrate that the CAS- equipped bank controller enables stable bank maneuvers at speeds up to 6 rad/s (1.83 m/s), where previous controllers fail, by dynamically limiting roll commands based on velocity and internal pressure.