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Model predictive obstacle avoidance control for leg/wheel mobile robots with optimized articulated leg configuration

机译:具有优化的关节腿配置的腿/轮移动机器人的模型预测性避障控制

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In this study, we propose a model predictive obstacle avoidance control for leg/wheel mobile robots with optimized articulated leg configuration. Using the proposed method, the robot can avoid obstacles and keep stability in narrow and complex spaces like indoor environments while the robot allocates wheels adapted to the surrounding environment. We optimize the angular velocities of joints and wheel driving speeds using model predictive control. Although our past related researches optimize the joint angles and wheel speeds separately, the proposed method optimizes these simultaneously. Thus, enhanced optimality of the entire robot system is expected to be achieved. We conduct numerical simulations of an actual mobile robot to verify efficacy and feasibility of the proposed method, which demonstrate that the proposed method is effective to avoid obstacles.
机译:在这项研究中,我们为具有优化的铰接式腿部构造的腿/轮移动机器人提出了一种模型预测性障碍回避控制。使用所提出的方法,机器人可以在狭窄而复杂的空间(如室内环境)中避开障碍物并保持稳定性,同时机器人可以分配适合周围环境的车轮。我们使用模型预测控制来优化关节的角速度和车轮驱动速度。尽管我们过去的相关研究分别对关节角度和车轮速度进行了优化,但所提出的方法却同时对它们进行了优化。因此,期望实现整个机器人系统的增强的最优性。我们对实际的移动机器人进行了数值模拟,以验证该方法的有效性和可行性,证明了该方法能够有效地避免障碍。

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