Context-Based Adaptation of In-Hand Slip Detection for Service Robots
| Autor: | Sven Schneider, Jose Sanchez, Gerhard K. Kraetzschmar, Paul G. Plöger, Nico Hochgeschwender |
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| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Engineering business.industry GRASP 02 engineering and technology Slip (materials science) Sensor fusion Robot control 020901 industrial engineering & automation Control and Systems Engineering Human–computer interaction Robot Torque sensor Computer vision Slippage Artificial intelligence business Tactile sensor |
| Zdroj: | IFAC-PapersOnLine. 49:266-271 |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2016.07.765 |
| Popis: | Mobile manipulators are intended to be deployed in domestic and industrial environments where they will carry out tasks that require physical interaction with the surrounding world, for example, picking or handing over fragile objects. In-hand slippage, i.e. a grasped object moving within the robot’s grasp, is inherent to many of these tasks and thus, a robot’s ability to detect a slippage is vital for executing a manipulation task successfully. In this paper, we develop a slip detection approach which is based on the robot’s tactile sensors, a force/torque sensor and a combination thereof. The evaluation of our approach, carried out on the Care-O-bot 3 platform, highly suggests that the actions and motions performed by the robot during grasping should be taken into account during slip detection for improved performance. Based on this insight, we propose an in-hand slip detection architecture that is able to adapt to the current robot’s actions at run time. |
| Databáze: | OpenAIRE |
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