Biped robots have plenty of benefits over wheeled, quadruped, or hexapod robots due to their ability to behave like human beings in tough and non-flat environments. Deformable terrain is another challenge for biped robots as it has to deal with sinkage and maintain stability without falling. In this study, we are proposing a Deep Deterministic Policy Gradient (DDPG) approach for motion control of a flat-foot biped robot walking on deformable terrain. We have considered a 7-link biped robot for our proposed approach. For soft soil terrain modeling, we have considered triangular Mesh to describe its geometry, where mesh parameters determine the softness of soil. All simulations have been performed on PyChrono, which can handle soft soil environments.

翻译：双足机器人因其在崎岖非平坦环境中具备类人行为能力，相较于轮式、四足或六足机器人具有诸多优势。可变形地形对双足机器人构成额外挑战，需应对下陷问题并保持不摔倒的稳定性。本研究提出采用深度确定性策略梯度（DDPG）方法，实现平足双足机器人在可变形地形上的运动控制。我们针对该方案采用了七连杆双足机器人模型。在软土地形建模方面，采用三角网格描述其几何特征，通过网格参数控制土壤软硬度。所有仿真均在可处理软土环境的PyChrono平台上完成。