Safe path and gait planning are essential for bipedal robots to navigate complex real-world environments. The prevailing approaches often plan the path and gait separately in a hierarchical fashion, potentially resulting in unsafe movements due to neglecting the physical constraints of walking robots. A safety-critical path must not only avoid obstacles but also ensure that the robot's gaits are subject to its dynamic and kinematic constraints. This work presents a novel approach that unifies path planning and gait planning via a Model Predictive Control (MPC) using the Linear Inverted Pendulum (LIP) model representing bipedal locomotion. This approach considers environmental constraints, such as obstacles, and the robot's kinematics and dynamics constraints. By using discrete-time Control Barrier Functions for obstacle avoidance, our approach generates the next foot landing position, ensuring robust walking gaits and a safe navigation path within clustered environments. We validated our proposed approach in simulation using a Digit robot in 20 randomly created environments. The results demonstrate improved performance in terms of safety and robustness when compared to hierarchical path and gait planning frameworks.

翻译：安全路径与步态规划对于双足机器人在复杂真实环境中导航至关重要。现有方法通常采用分层架构分别规划路径与步态，但因忽略步行机器人的物理约束，可能导致不安全运动。安全关键路径不仅需要避开障碍物，还必须确保机器人的步态符合其动力学与运动学约束。本文提出一种新方法，通过基于线性倒立摆（LIP）模型的模型预测控制（MPC）统一路径规划与步态规划。该方法综合考虑了环境约束（如障碍物）以及机器人的运动学与动力学约束。通过采用离散时间控制屏障函数进行避障，我们的方法可生成下一步落足位置，确保在密集环境中实现稳健的行走步态与安全导航路径。我们在20个随机生成环境中使用Digit机器人进行仿真验证。结果表明，与分层路径与步态规划框架相比，本方法在安全性与鲁棒性方面具有更优性能。