Research/ ORBITAL ROBOTICS
Human Initiated Grasp Space Exploration Algorithm for an Underactuated Robot Gripper Using Variational Autoencoder
Clément Rolinat, Mathieu Grossard, Saifeddine Aloui, Christelle Godin
Manipulation & GraspingOpenAlex topic: Robot Manipulation and Learning · Learning-based MethodsOpenAlex topic: Reinforcement Learning in Robotics · Design, Mechanisms & HardwareOpenAlex topic: Soft Robotics and Applications
arXivcs.ROOpenAlexRobot Manipulation and Learning · Reinforcement Learning in Robotics · Soft Robotics and Applications
Grasp planning and most specifically the grasp space exploration is still an open issue in robotics. This article presents an efficient procedure for exploring the grasp space of a multifingered adaptive gripper for generating reliable grasps given a known object pose. This procedure relies on a limited dataset of manually specified expert grasps, and use a mixed analytic and data-driven approach based on the use of a grasp quality metric and variational autoencoders. The performances of this method are assessed by generating grasps in simulation for three different objects. On this grasp planning task, this method reaches a grasp success rate of 99.91% on 7000 trials.
Comments: accepted at ICRA 2021 conference. arXiv admin note: substantial text overlap with arXiv:2109.08504
Journal ref: 2021 IEEE International Conference on Robotics and Automation (ICRA)