Name
Abstract | ||
|---|---|---|
Like humans, robots that need semantic perception and accurate estimation of the environment can increase their knowledge through active interaction with objects. This paper proposes a novel method for 3D object modeling for a robot manipulator with an eye-in-hand laser range sensor. Since the robot can only perceive the environment from a limited viewpoint, it actively manipulates a target object and generates a complete model by accumulation and registration of partial views. Three registration algorithms are investigated and compared in experiments performed in cluttered environments with complex rigid objects made of multiple parts. A data structure based on proximity graph, that encodes neighborhood relations in range scans, is also introduced to perform efficient range queries. The proposed method for 3D object modeling is applied to perform task-level manipulation. Indeed, once a complete model is available the object is segmented into its constituent parts and categorized. Object sub-parts that are relevant for the task and that afford a grasping action are identified and selected as candidate regions for grasp planning. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s10846-014-0045-6 | Journal of Intelligent and Robotic Systems |
Keywords | Field | DocType |
Active exploration of the environment,Range sensing,Robot manipulation | Data structure,Computer vision,Graph,Grasp planning,Range query (data structures),Object model,Artificial intelligence,Engineering,Robot manipulator,Robot,Perception | Journal |
Volume | Issue | ISSN |
76 | 3-4 | 0921-0296 |
Citations | PageRank | References |
4 | 0.46 | 52 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jacopo Aleotti | 1 | 259 | 29.76 |
| Dario Lodi Rizzini | 2 | 83 | 12.58 |
| Stefano Caselli | 3 | 314 | 36.32 |