This paper presents a framework that allows online dynamic-stability-constrained optimal trajectory planning of a mobile manipulator robot working on rough terrain. First, the kinematics model of a mobile manipulator robot, and the Zero Moment Point (ZMP) stability measure are presented as theoretical background. Then, a sampling-based quasi-static planning algorithm modified for stability guarantee and traction optimization in continuous dynamic motion is presented along with a mathematical proof. The robot's quasi-static path is then used as an initial guess to warm-start a nonlinear optimal control solver which may otherwise have difficulties finding a solution to the stability-constrained formulation efficiently. The performance and computational efficiency of the framework are demonstrated through an application to a simulated timber harvesting mobile manipulator machine working on varying terrain. The results demonstrate feasibility of online trajectory planning on varying terrain while satisfying the dynamic stability constraint.

翻译：本文提出了一个框架,允许对在崎岖的地形上工作的移动操纵机器人进行在线动态稳定、受限制的最佳轨迹规划。 首先,移动操纵机器人的运动模型和零动力点稳定性测量作为理论背景。 然后,在提供数学证据的同时,还提出了为稳定性保障和连续动态运动的牵引优化而修改的基于抽样的准静态规划算法。 然后,机器人的准静态路径被用作一个初步的猜测,以温暖启动一个非线性最佳控制解析器,否则它可能难以找到稳定受限制的配方的解决方案。框架的性能和计算效率通过在不同的地形上运行的模拟木材采伐移动操纵机的应用得到证明。 结果表明,在满足动态稳定性制约的同时,在不同的地形上进行在线轨迹规划是可行的。