A Laser-based Dual-arm System for Precise Control of Collaborative Robots
This addresses the problem of limited precision for collaborative robots in high-precision tasks like watch-making, though it is incremental as it builds on existing sensing and registration methods.
The paper tackles the lack of precision in collaborative robots by using a dual-arm system with laser-based sensing to measure and compensate for pose errors, achieving high-precision assembly as validated in tasks like needle threading with a 150μm thread and 300μm hole.
Collaborative robots offer increased interaction capabilities at relatively low cost but in contrast to their industrial counterparts they inevitably lack precision. Moreover, in addition to the robots' own imperfect models, day-to-day operations entail various sources of errors that despite being small rapidly accumulate. This happens as tasks change and robots are re-programmed, often requiring time-consuming calibrations. These aspects strongly limit the application of collaborative robots in tasks demanding high precision (e.g. watch-making). We address this problem by relying on a dual-arm system with laser-based sensing to measure relative poses between objects of interest and compensate for pose errors coming from robot proprioception. Our approach leverages previous knowledge of object 3D models in combination with point cloud registration to efficiently extract relevant poses and compute corrective trajectories. This results in high-precision assembly behaviors. The approach is validated in a needle threading experiment, with a 150μm thread and a 300μm hole, and a USB insertion task using two 7-axis Panda robots.