Abstract In this study, we propose a method that can be used to enhance the configuration of mobile robots equipped with articulated legs and wheels by simultaneously optimizing leg joint angles and wheel positions using model predictive control (MPC). To present a manageable expression for MPC, the kinematics of a robot that has highly articulated legs with wheels at their ends are represented as serially connected constrained links. The other end of the leg is constrained by its position relative to the robot body. To actively allocate and adapt movements to the surrounding environment, we use a potential field method applied to each wheel. Our method is based on the following strategy. First, we will design a simple collision-free reference path for a point mass, and then we will apply MPC to induce optimal path tracking control that balances the input and artificial potential costs. This will allow the robot to adapt its wheel position configurations to the surrounding environment. Based on that strategy, we conducted numerical simulations and experiments using an actual mobile robot to verify the efficacy and feasibility of our proposed method, the results of which demonstrated its effective ability to adaptively configure its articulated legs in ways that allowed the robot to avoid obstacles.

中文翻译：

---

平面腿轮移动机器人柔性避障优化配置控制

摘要 在这项研究中，我们提出了一种方法，该方法可用于通过使用模型预测控制 (MPC) 同时优化腿部关节角度和车轮位置来增强配备铰接腿和车轮的移动机器人的配置。为了呈现 MPC 的可管理表达式，机器人的运动学表示为串联连接的约束链接，该机器人具有高度铰接的腿，其末端带有轮子。腿的另一端受其相对于机器人身体的位置的约束。为了主动分配和适应周围环境的运动，我们使用应用于每个车轮的势场方法。我们的方法基于以下策略。首先，我们将为点质量设计一个简单的无碰撞参考路径，然后我们将应用 MPC 来诱导最佳路径跟踪控制，以平衡输入和人工潜在成本。这将使机器人能够根据周围环境调整其车轮位置配置。基于该策略，我们使用实际移动机器人进行了数值模拟和实验，以验证我们提出的方法的有效性和可行性，结果证明其有效地以允许机器人避开障碍物的方式自适应配置其关节腿的能力.