We describe a force-controlled robotic gripper with built-in tactile and 3D perception. We also describe a complete autonomous manipulation pipeline consisting of object detection, segmentation, point cloud processing, force-controlled manipulation, and symbolic (re)-planning. The design emphasizes versatility in terms of applications, manufacturability, use of commercial off-the-shelf parts, and open-source software. We validate the design by characterizing force control (achieving up to 32N, controllable in steps of 0.08N), force measurement, and two manipulation demonstrations: assembly of the Siemens gear assembly problem, and a sensor-based stacking task requiring replanning. These demonstrate robust execution of long sequences of sensor-based manipulation tasks, which makes the resulting platform a solid foundation for researchers in task-and-motion planning, educators, and quick prototyping of household, industrial and warehouse automation tasks.
@article{arxiv.2402.06018,
title = {A versatile robotic hand with 3D perception, force sensing for autonomous manipulation},
author = {Nikolaus Correll and Dylan Kriegman and Stephen Otto and James Watson},
journal= {arXiv preprint arXiv:2402.06018},
year = {2024}
}
Comments
RSS Workshop on Perception and Manipulation Challenges for Warehouse Automation, Daejeon, Korea