This paper presents a planning pipeline framework for locomotion in rope-assisted robots climbing vertical surfaces. The proposed framework is formulated as a bi-level optimization scheme that addresses a mixed-integer problem: selecting feasible terrain regions for landing while simultaneously optimizing the control inputs, namely rope tensions and leg forces, and landing location. The outer level of the optimization is solved using the Cross-Entropy Method, while the inner level relies on gradient-based nonlinear optimization to compute dynamically feasible motions. The approach is validated on a novel climbing robot platform, ALPINE, across a variety of challenging terrain configurations.

翻译：本文提出了一种用于绳助式机器人攀爬垂直表面的运动规划流水线框架。该框架采用双层优化方案构建，旨在解决混合整数问题：在优化控制输入（绳张力与腿力）和落足位置的同时，选择可行的地形着陆区域。外层优化采用交叉熵法求解，内层优化则依赖基于梯度的非线性优化方法计算动态可行的运动轨迹。该方案在新型攀爬机器人平台ALPINE上经过多种复杂地形配置的验证。