实时规划双足机器人步态与质心轨迹，速度超十倍于现有方法。
Real-time Coupled Centroidal Motion and Footstep Planning for Biped Robots
- 用可选落脚点建模动态步态规划，通过重加权l1范数逼近选择限制。
- 2秒规划窗口、13个时间步、每步20个可选表面，142毫秒完成求解。
- 无需预设步态，自动发现合理行走模式，适合复杂地形仿真测试。
本文提出一种算法，针对类弹簧倒立摆（SLIP）双足机器人模型，实现远超实时的质心运动与步态规划。通过将环境中的每个点视为潜在落脚点，可施加力以维持质心在期望轨迹上；每步最多选择两个落脚点，采用迭代重加权l1范数近似该基数约束。结合角动量约束的线性化近似，构建出可求解的二次规划问题，实现接触序列与质心轨迹的联合优化，并支持自动步态发现。在2秒规划时长、13个时间步、每步20个可用表面的条件下，仅需142毫秒即可求解，较文献中同类方法快约十倍。我们在多种模拟环境中验证了该方法的通用性。
原文摘要 · Abstract (English)
This paper presents an algorithm that finds a centroidal motion and footstep plan for a Spring-Loaded Inverted Pendulum (SLIP)-like bipedal robot model substantially faster than real-time. This is achieved with a novel representation of the dynamic footstep planning problem, where each point in the environment is considered a potential foothold that can apply a force to the center of mass to keep it on a desired trajectory. For a biped, up to two such footholds per time step must be selected, and we approximate this cardinality constraint with an iteratively reweighted $l_1$-norm minimization. Along with a linearizing approximation of an angular momentum constraint, this results in a quadratic program can be solved for a contact schedule and center of mass trajectory with automatic gait discovery. A 2 s planning horizon with 13 time steps and 20 surfaces available at each time is solved in 142 ms, roughly ten times faster than comparable existing methods in the literature. We demonstrate the versatility of this program in a variety of simulated environments.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。