Name
Title | ||
|---|---|---|
Image-Based Visual Servoing Controller For Multirotor Aerial Robots Using Deep Reinforcement Learning |
Abstract | ||
|---|---|---|
In this paper, we propose a novel Image-Based Visual Servoing (IBVS) controller for multirotor aerial robots based on a recent deep reinforcement learning algorithm named Deep Deterministic Policy Gradients (DDPG). The proposed RL-IBVS controller is successfully trained in a Gazebo-based simulation scenario in order to learn the appropriate IBVS policy for directly mapping a state, based on errors in the image, to the linear velocity commands of the aerial robot. A thorough validation of the proposed controller has been conducted in simulated and real flight scenarios, demonstrating outstanding capabilities in object following applications. Moreover, we conduct a detailed comparison of the RL-IBVS controller with respect to classic and partitioned IBVS approaches. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IROS.2018.8594249 | 2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) |
Field | DocType | ISSN |
Constant linear velocity,Computer vision,Control theory,Task analysis,Computer science,Control engineering,Visual servoing,Artificial intelligence,Deep learning,Robot,Multirotor,Reinforcement learning | Conference | 2153-0858 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos Sampedro | 1 | 54 | 6.46 |
| Alejandro Rodriguez-Ramos | 2 | 20 | 2.44 |
| Ignacio Gil | 3 | 1 | 0.36 |
| Luis Mejias | 4 | 143 | 15.42 |
| Pascual Campoy | 5 | 436 | 46.75 |