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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:考虑基于编码器内径信息的机器人运动的不确定性,避免两轮差动机器人的障碍

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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:克服移动机器人安全可靠导航的不同类型的不确定性非常重要。不确定性来源可以分为识别,运动和环境来源。虽然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注意力很少。本研究表明了如何通过实验定量建模机器人运动的不确定性。虽然实际运动不确定性受到各种因素的影响,但本研究侧重于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并不可忽略不可忽略。本文通过反映实验运动不确定性提出了一种新的运动控制方案,以可靠的障碍避免。所提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的碰撞避免至关重要。所提出的仿真结果表明,当运动的不确定度高时,机器人不能通过碰撞风险而移动。该研究表明,该方法准确地反映了运动不确定性,并通过机器人的导航效率平衡碰撞安全性。

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