论文标题
大型升级的非线性轨迹优化:应用于人形机器人地图集
Non-Linear Trajectory Optimization for Large Step-Ups: Application to the Humanoid Robot Atlas
论文作者
论文摘要
对于人形机器人来说,执行大型升级是一项具有挑战性的任务。它要求机器人在其可到达工作区的极限上执行动作,同时努力将其身体移动到障碍物上。本文提出了一种非线性轨迹优化方法,用于生成升级运动。我们采用简化的质心动力学模型来生成可行的质量轨迹中心,旨在减少升级运动所需的扭矩。两脚的接触的激活和停用被明确考虑。计划者的输出是质量轨迹的中心,每个步行阶段的最佳持续时间。这些所需的值通过确定一组所需的关节扭矩的全身控制器稳定。我们通过实验表明,通过使用轨迹优化技术,在执行升级运动时,全尺寸类人动物机器人地图集所需的最大扭矩可将其降低到20%。
Performing large step-ups is a challenging task for a humanoid robot. It requires the robot to perform motions at the limit of its reachable workspace while straining to move its body upon the obstacle. This paper presents a non-linear trajectory optimization method for generating step-up motions. We adopt a simplified model of the centroidal dynamics to generate feasible Center of Mass trajectories aimed at reducing the torques required for the step-up motion. The activation and deactivation of contacts at both feet are considered explicitly. The output of the planner is a Center of Mass trajectory plus an optimal duration for each walking phase. These desired values are stabilized by a whole-body controller that determines a set of desired joint torques. We experimentally demonstrate that by using trajectory optimization techniques, the maximum torque required to the full-size humanoid robot Atlas can be reduced up to 20% when performing a step-up motion.