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Obstacle Avoidance of Two-Wheel Differential Robots Considering the Uncertainty of Robot Motion on the Basis of Encoder Odometry Information

机译:基于编码器里程表信息的考虑机器人运动不确定性的两轮差分机器人的避障

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摘要

It is important to overcome different types of uncertainties for the safe and reliable navigation of mobile robots. Uncertainty sources can be categorized into recognition, motion, and environmental sources. Although several challenges of recognition uncertainty have been addressed, little attention has been paid to motion uncertainty. This study shows how the uncertainties of robot motions can be quantitatively modeled through experiments. Although the practical motion uncertainties are affected by various factors, this research focuses on the velocity control performance of wheels obtained by encoder sensors. Experimental results show that the velocity control errors of practical robots are not negligible. This paper proposes a new motion control scheme toward reliable obstacle avoidance by reflecting the experimental motion uncertainties. The presented experimental results clearly show that the consideration of the motion uncertainty is essential for successful collision avoidance. The presented simulation results show that a robot cannot move through narrow passages owing to a risk of collision when the uncertainty of motion is high. This research shows that the proposed method accurately reflects the motion uncertainty and balances the collision safety with the navigation efficiency of the robot.
机译:克服不同类型的不确定性对于移动机器人的安全可靠导航非常重要。不确定性源可以分类为识别,运动和环境源。尽管已经解决了识别不确定性的几个挑战,但是对运动不确定性的关注却很少。这项研究表明,如何通过实验对机器人运动的不确定性进行定量建模。尽管实际的运动不确定性受各种因素影响,但本研究着重于通过编码器传感器获得的车轮的速度控制性能。实验结果表明,实用机器人的速度控制误差不可忽略。通过反映实验运动的不确定性,本文提出了一种新的面向可靠避障的运动控制方案。给出的实验结果清楚地表明,对运动不确定性的考虑对于成功避免碰撞至关重要。仿真结果表明,当运动不确定性较高时,由于存在碰撞的危险,机器人无法在狭窄的通道中移动。研究表明,该方法能够准确反映运动的不确定性,并在碰撞安全性与机器人导航效率之间取得平衡。

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