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Wheel velocity obstacles for differential drive robot navigation

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In this paper, we deal with the real-time navigation problem of a differential drive robot in dynamic environments. As a rule, the robot is controlled by wheel velocity commands at sampling intervals and moves along a straight line or a circular arc in accordance with those commands. | Journal of Automation and Control Engineering Vol. 3, No. 5, October 2015 Wheel Velocity Obstacles for Differential Drive Robot Navigation Jae D. Jeon and Beom H. Lee Department of Electrical and Computer Engineering, Seoul National University, Seoul, the Republic of Korea Email: {innocent88, bhlee}@snu.ac.kr Abstract—In this paper, we deal with the real-time navigation problem of a differential drive robot in dynamic environments. As a rule, the robot is controlled by wheel velocity commands at sampling intervals and moves along a straight line or a circular arc in accordance with those commands. Thus, we define the wheel velocity obstacle, which is a set of all the left and right wheel velocity pairs that induce collisions with obstacles within a given time horizon. Also, a navigation strategy is suggested that will allow the robot to reach its destination without colliding with obstacles. Our algorithm was found to outperform previously released collision avoidance algorithms in terms of safety through Monte Carlo simulations. robots handling a deformable object avoid collisions in an environment. These two methods was limited in that they could be applied to only static environments. Ideal Holonomic Trajectory T w Real Trajectory Index Terms—collision avoidance, motion planning, velocity obstacles, differential drive robot I. Figure 1. Tracking error T between the ideal holonomic trajectory and the real trajectory. The robot moves in the direction. On the contrary, [7] and [8] took dynamic obstacles into consideration. They defined Dynamic Velocity Space (DVS) that contained the potential collision information, which is the robot’s velocity and the corresponding collision time, and utilized the space to find the optimal command. In addition, [9] generalized the velocity obstacle [3] to deal with the constraints of a car-like robot by calculating the minimum distance between the robot and obstacle for randomly sampled controls. Reference [10] .