Name
Title | ||
|---|---|---|
On the Way from Lightweight to Powerful Intelligence: A Heterogeneous Multi-Robot Social System with IoT Devices |
Abstract | ||
|---|---|---|
As robots play an increasingly important role in people’s lives, researchers are working on robotic vehicles with powerful intelligence. However, a problem that cannot be ignored is resource constraints on the edge. Considering the gaming issues of resource constraints and intelligence level, we focus on robots with limited computing resources and propose an idea of changing from lightweight to powerful intelligence for a smart robotic system. Firstly, we design a series of ultra-lightweight algorithms according to the lightweight resource Limitation. Second, we collaborate the ultra-lightweight algorithms through a centralized-distributed architecture to achieve intelligent upgrading of the whole system. Then, by maximizing the use of resources and information, we accomplish a heterogeneous ultra-lightweight multi-robotic collaborative system. Finally, the presented architecture has been applied to realize a lightweight simultaneous localization and mapping (SLAM) system. Experimentally, the ultra-lightweight algorithm achieves 900 fps on the server experimental platform. Since there have been less heterogeneous collaborative methods, we further compared it with the state-of-the-art homogeneous collaborative system and proved that the accuracy of our proposed system was improved by 45.98%. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/CASE49997.2022.9926515 | 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) |
Keywords | DocType | ISSN |
powerful intelligence,heterogeneous multirobot social system,robotic vehicles,resource constraints,intelligence level,computing resources,smart robotic system,ultra-lightweight algorithm,lightweight resource Limitation,intelligent upgrading,heterogeneous ultra-lightweight multirobotic collaborative system,lightweight simultaneous localization,heterogeneous collaborative methods,state-of-the-art homogeneous collaborative system | Conference | 2161-8070 |
ISBN | Citations | PageRank |
978-1-6654-9043-6 | 0 | 0.34 |
References | Authors | |
12 | 10 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qian Zhang | 1 | 17 | 21.63 |
| Ruiyang Quan | 2 | 0 | 0.34 |
| Siqin Qimuge | 3 | 0 | 0.34 |
| Rui Wei | 4 | 0 | 0.34 |
| Xin Zan | 5 | 0 | 0.34 |
| Fangshi Wang | 6 | 21 | 4.74 |
| Changchuan Chen | 7 | 0 | 0.34 |
| Qi Wei | 8 | 49 | 20.68 |
| Xin-Jun Liu | 9 | 155 | 32.61 |
| Fei Qiao | 10 | 94 | 35.38 |