This paper addresses exhaustive coverage path planning of a mining robot based on cellular decomposition in minable area. For this work, the followings are done. First, the map of minable area is decomposed into cells by exact cell decomposition. Second, the coverage path is generated using back-and-forth motion. Third, direction of coverage path and generating graph path using proposed special spanning tree is considered to get minimum distance of moving path. The exhaustive coverage path is obtained by combining coverage path and moving path. Fourth, a controller is designed for a two-wheeled robot to track the exhaustive coverage path generated by path planning method. Finally, simulation and experimental results can prove efficiency of the proposed exhaustive coverage path planning method.
This paper introduces omni-directional walking control of a six-legged robot (6LR). The 6LR consists of its body, six legs with four links and four rotational joints. The followings are done for this task. First, the walking gait of the 6LR is chosen. Second, modeling for one leg with four links and four rotational joints of the 6LR is proposed. It is difficult and complex to get the angles of four rotational joints in the case of using inverse kinematics. To solve this problem, differential kinematics algorithm is used to generate omni-directional walking trajectory of a leg based on back-stepping control using Lyapunov stability. Finally, simulation results for walking motion of one leg of the 6LR are shown to prove the effectiveness and applicability of the proposed controller.
This paper proposes a tracking controller for obstacle avoidance of an omni-directional mobile vehicle (OMV) using potential function method through a ceiling-mounted camera system. To do this task, the followings were done. At first, for image processing, a ceiling-mounted camera system was installed to get images. The goal point and obstacles were separated and recognized by a color recognition method. Second, potential function method was proposed to generate the shortest path to avoid obstacles from the start point to the goal point. The mobile platform is a mecanum wheel omni-directional vehicle. Third, the tracking controller is designed for the OMV to track a trajectory generated by a path planning algorithm based on the backstepping method using Lyapunov function. Finally, the simulation results were presented to show the effectiveness of the proposed trajectory planning algorithm and tracking controller for obstacle avoidance of the OMV.
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