Abstract
So far, autonomous order picking (commissioning) systems have not been able to meet the stringent demands regarding speed, safety, and accuracy of real-world warehouse automation, resulting in reliance on human workers. In this letter, we target the next step in autonomous robot commissioning: automatizing the currently manual order picking procedure. To this end, we investigate the use case of autonomous picking and palletizing with a dedicated research platform and discuss lessons learned during testing in simplified warehouse settings. The main theoretical contribution is a novel grasp representation scheme which allows for redundancy in the gripper pose placement. This redundancy is exploited by a local, prioritized kinematic controller which generates reactive manipulator motions on-the-fly. We validated our grasping approach by means of a large set of experiments, which yielded an average grasp acquisition time of 23.5 s at a success rate of 94.7%. Our system is able to autonomously carry out simple order picking tasks in a human-safe manner, and as such serves as an initial step toward future commercial-scale in-house logistics automation solutions.
| Original language | English |
|---|---|
| Article number | 7387707 |
| Pages (from-to) | 546-553 |
| Number of pages | 8 |
| Journal | IEEE Robotics and Automation Letters |
| Volume | 1 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2016 |
| Externally published | Yes |
Keywords
- Logistics
- autonomous vehicle navigation
- grasping
- mobile manipulation
- robot safety
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