用凸优化生成人形机器人多接触导航轨迹，3秒内完成复杂环境行走规划。
Guiding Collision-Free Humanoid Multi-Contact Locomotion using Convex Kinematic Relaxations and Dynamic Optimization
- 将避障路径规划转为凸优化，实现快速生成近可行轨迹
- 在仿真中3秒内完成三类人形机器人穿越高门槛门的多接触运动规划
- 适合需要动态稳定性和实时性的复杂地形行走场景
人形机器人依赖多接触规划器在多样环境中导航，包括非结构化且高度受限的环境。为在合理时间内生成稳定多接触计划，多数规划器假设静态稳定运动或使用降阶模型，但这些方法在存在大障碍物或接近运动与动力学极限时可能不可行。为此，我们提出一种新多接触框架，利用近期将无碰撞路径规划松弛为凸优化问题的进展，扩展至适用于人形多接触导航。该方法生成近可行轨迹作为动态轨迹优化器的引导，整体克服了上述局限。我们在仿真中评估该计算方法，展示三类不同尺寸的人形机器人通过高抬高的海军膝跳门，使用所提框架在数秒内生成包含多个接触状态的运动计划，并保证关节空间内的动态可行性。
原文摘要 · Abstract (English)
Humanoid robots rely on multi-contact planners to navigate a diverse set of environments, including those that are unstructured and highly constrained. To synthesize stable multi-contact plans within a reasonable time frame, most planners assume statically stable motions or rely on reduced order models. However, these approaches can also render the problem infeasible in the presence of large obstacles or when operating near kinematic and dynamic limits. To that end, we propose a new multi-contact framework that leverages recent advancements in relaxing collision-free path planning into a convex optimization problem, extending it to be applicable to humanoid multi-contact navigation. Our approach generates near-feasible trajectories used as guides in a dynamic trajectory optimizer, altogether addressing the aforementioned limitations. We evaluate our computational approach showcasing three different-sized humanoid robots traversing a high-raised naval knee-knocker door using our proposed framework in simulation. Our approach can generate motion plans within a few seconds consisting of several multi-contact states, including dynamic feasibility in joint space.
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