  This paper introduces a novel NMPC formulation for real-time obstacle
avoidance on heavy equipment by modeling both vehicle and obstacles as convex
superellipsoids. The combination of this approach with the separating
hyperplane theorem and Optimization Engine (OpEn) allows to achieve efficient
obstacle avoidance in autonomous heavy equipment and robotics. We demonstrate
the efficacy of the approach through simulated and experimental results,
showcasing a skid-steer loader's capability to navigate in obstructed
environments.
