Abstract
In this paper we present our approach on path planning for a 2DOF serial robotic arm without constructing a kinematic model of it. Our approach is different from the standard approach, where you have to know the robot’s kinematic parameters such as length of elements, through the fact that we do not use a kinematic model to position or execute path planning for the arm, but rather rely on visual information from a camera to complete the task. We consider only the positions of the end-effector when planning the path, velocities are ignored. The problem to be solved in this paper is formulated as find a path that positions the robot’s end-effector at the target position and avoids any obstacles. Our approach on solving this problem is to sample the workspace (randomly or by sweeping it incrementally) in order to get a correspondence between the end-effector position to the corresponding joint angle values (equivalent to deriving the kinematic model of the robot, but not through equations) and then use the subset of points as a look-up table to compute a path between the points that take us closest to the target.
To prove our concept we designed a system that consists of a 3D printed 2 DOF arm, driven by Dynamixel servos, Videocamera, OpenCV and Python. The precise positioning of the end-effector at the target position is achieved using algorithms presented in the literature and in our previous work.
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Acknowledgment
This work was supported by research grant GNaC2018 - ARUT, no. 1364/01.02.2019, financed by Politehnica University of Timisoara.
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Moldovan, C., Ciupe, V., Filipescu, H., Kristof, R., Dolga, V. (2021). Model-Free Continuous to Discrete Workspace Transformation and Path Planning of a 2DOF Serial Arm for Visual Obstacle Avoidance. In: Lovasz, EC., Maniu, I., Doroftei, I., Ivanescu, M., Gruescu, CM. (eds) New Advances in Mechanisms, Mechanical Transmissions and Robotics . MTM&Robotics 2020. Mechanisms and Machine Science, vol 88. Springer, Cham. https://doi.org/10.1007/978-3-030-60076-1_23
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DOI: https://doi.org/10.1007/978-3-030-60076-1_23
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