Name
Abstract | ||
|---|---|---|
This work investigates an over-arching question: how can an immersive virtual environment be connected with its intelligent physical counterpart to allow for a more efficient man-machine collaboration. To this end, an immersive user interface for the purpose of robot tele-operation is designed. A large amount of sensory data is utilized to build models of the world and its inhabitants in a way that is intuitive to the operator and accurately represents the robot's real-world state and environment. The game client is capable of handling multiple users, much like a traditional multiplayer game, while visualizing multiple robotic agents operating within the real world. The proposed Virtual Environment for Tele-Operation (VETO) architecture is a tele-operation system that provides a feature-rich framework to implement robotic agents into an immersive end-user game interface. Game levels are generated dynamically on a Graphic Processing Unit or GPU-accelerated server based on real-world sensor data from the robotic agents. A set of user studies are conducted to validate the performance of the proposed architecture compared to traditional tele-robotic applications. The experimental results show significant improvements in both task completion time and task completion rate over traditional tools. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/robotics7020026 | ROBOTICS |
Keywords | Field | DocType |
immersive virtual environments,tele-operation,immersive game clients,dynamic level generation,sensory fusion,autonomous operation | Architecture,Virtual machine,Control engineering,Human–computer interaction,Game client,Immersion (virtual reality),Engineering,User interface,Robot,Multiplayer game,Veto | Journal |
Volume | Issue | ISSN |
7 | 2.0 | 2218-6581 |
Citations | PageRank | References |
1 | 0.37 | 5 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brandon Wilson | 1 | 1 | 2.06 |
| Matthew Bounds | 2 | 1 | 1.39 |
| David McFadden | 3 | 1 | 0.37 |
| Jace Regenbrecht | 4 | 1 | 0.37 |
| Loveth Ohenhen | 5 | 1 | 0.37 |
| Alireza Tavakkoli | 6 | 168 | 15.97 |
| Donald A. Loffredo | 7 | 7 | 2.83 |