joek5555/tensegrity-RL

The project is a personal or academic experiment with zero stars and very low activity, making it a 'tutorial-level' repository in the context of competitive intelligence. While tensegrity robotics is a complex and niche field, this repository lacks the community traction, documentation, or infrastructure-grade features to be considered defensible. It likely reimplements known RL strategies (like PPO or SAC) for a specific tensegrity structural model. Frontier labs like OpenAI or Google DeepMind are unlikely to compete directly in this niche because tensegrity is physically specialized and not currently part of the 'general-purpose humanoid' push; however, any progress made here could be trivially superseded by more robust simulation frameworks like NVIDIA's Isaac Gym or NASA's NTRT (NASA Tensegrity Robotics Toolkit). The 'displacement horizon' is short because a more active research group could publish a superior, better-documented version of this work in a single conference cycle.