Trajectory Tracking Control of a Flexible Spine Robot, With and Without a Reference Input

The ULTRA Spine project is a specialized research artifact associated with a 2018 ArXiv paper. With 0 stars and 9 forks over nearly 8 years, it lacks any commercial or open-source momentum. The defensibility is extremely low (2) as it represents a specific point-in-time implementation of MPC for a niche hardware architecture (tensegrity backbones). While tensegrity robotics is technically complex, this code functions as a reference implementation for academic replication rather than a deployable library. Frontier labs (OpenAI/Google) have zero interest in specific tensegrity control logic, preferring general-purpose reinforcement learning (RL) frameworks that can learn these dynamics without explicit MPC modeling. In the current robotics landscape, classical MPC for underactuated systems is being rapidly displaced by Deep Reinforcement Learning (DRL) and Sim-to-Real techniques (e.g., NVIDIA's Isaac Gym), making the displacement horizon for this specific approach very short. The 'moat' here is purely the niche domain expertise required to build the physical robot, not the provided software.