Modeling and Trajectory Optimization for Standing Long Jumping of a Quadruped with A Preloaded Elastic Prismatic Spine
This work addresses performance enhancement in legged robotics, but it is incremental as it builds on existing quadruped models with spinal compliance.
The paper tackled the problem of improving standing jump performance in quadrupedal robots by introducing an elastic prismatic spine model and optimizing trajectories, finding that a less stiff spring enhances jumping distance by enabling more motor power at the cost of energy efficiency.
This paper presents a novel methodology to model and optimize trajectories of a quadrupedal robot with spinal compliance to improve standing jump performance compared to quadrupeds with a rigid spine. We introduce an elastic model for a prismatic robotic spine that is actively preloaded and mechanically lock-enabled at initial and maximum length, and develop a constrained trajectory optimization method to co-optimize the elastic parameters and motion trajectories toward enhanced jumping distance. Results reveal that a less stiff spring is likely to facilitate jumping performance not as a direct propelling source but as a means to unleash more motor power for propelling by trading-off overall energy efficiency. We also visualize the impact of spring coefficients on the overall optimization routine from energetic perspectives to identify the suitable parameter region.