Name
Abstract | ||
|---|---|---|
Automated guided vehicles operation in human populated factory environments is a challenging task, especially when there is a demand to operate without following fixed paths defined by guide wires, magnetic tape, magnets, or transponders embedded in the floor. The paper at hand introduces a vision-based method enabling safe and autonomous operation of pallet moving vehicles that accommodate pallet detection, pose estimation, docking control and pallet pick up in such industrial environments. A dedicated perception topology relying on monocular vision and laser-based measurements has been applied and installed on-board a novel robotic pallet truck. Pallet detection and pose estimation are performed in two steps. Firstly, a deep neural network is used for the fast isolation of pallets' regions of interest and, secondly, model-based geometrical pattern matching on point cloud data is applied to extract the pallet pose. Robot alignment with candidate pallet is performed with a dedicated visual servoing controller. The developed method has been extensively evaluated both in simulated and real industrial environments with the pallet truck and proved to have real-time performance achieving increased accuracy in navigation, pallet detection and pick-up. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IROS51168.2021.9636270 | 2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) |
DocType | ISSN | Citations |
Conference | 2153-0858 | 0 |
PageRank | References | Authors |
0.34 | 0 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Efthimios Tsiogas | 1 | 0 | 1.01 |
| Ioannis Kleitsiotis | 2 | 0 | 1.01 |
| Ioannis Kostavelis | 3 | 0 | 0.34 |
| Andreas Kargakos | 4 | 39 | 3.63 |
| Dimitris Giakoumis | 5 | 0 | 0.34 |
| Marc Bosch-Jorge | 6 | 0 | 0.34 |
| Raquel Julia Ros | 7 | 0 | 0.34 |
| Rafa López Tarazón | 8 | 0 | 0.34 |
| Spiridon Likothanassis | 9 | 0 | 0.68 |
| Dimitrios Tzovaras | 10 | 1377 | 205.82 |