Name
Abstract | ||
|---|---|---|
Many of today's mobile robots are supposed to perform everyday manipulation tasks autonomously. However, in large-scale environments, a task-related object might be out of the robot's reach. Hence, the robot first has to search for the object in its environment before it can perform the task.In this paper, we present a decision-theoretic approach for searching objects in large-scale environments using probabilistic environment models and utilities associated with object locations. We demonstrate the feasibility of our approach by integrating it into a robot system and by conducting experiments where the robot is supposed to search different objects with various strategies in the context of fetch-and-delivery tasks within a multi-level building. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICRA.2012.6224965 | 2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA) |
Keywords | Field | DocType |
mobile robots,semantics,databases,decision theory,mobile robot,probability,elevators,probabilistic logic,robots | Social robot,Computer science,Control engineering,Human–computer interaction,Decision theory,Artificial intelligence,Probabilistic logic,Robotic systems,Computer vision,Elevator,Robot,Semantics,Mobile robot | Conference |
Volume | Issue | ISSN |
2012 | 1 | 1050-4729 |
Citations | PageRank | References |
12 | 0.73 | 8 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lars Kunze | 1 | 157 | 11.60 |
| Michael Beetz | 2 | 3784 | 284.03 |
| Manabu Saito | 3 | 12 | 0.73 |
| Haseru Azuma | 4 | 12 | 0.73 |
| Kei Okada | 5 | 534 | 118.08 |
| Masayuki Inaba | 6 | 2186 | 410.27 |