Name
Abstract | ||
|---|---|---|
A multi-fingered robot hand receives much attention in various fields. We have developed the multi-fingered robot hand with the multi-axis force/torque sensors. For stable transportation, the robot hand must pick up an object without dropping it and places it without damaging it. This paper deals with a pick-up motion based on vision and tactile information by the eveloped robot hand. Here, the robot hand learns a posture for picking an object up by using tactile values and the visual image in advance, then determines the number of fingers in pick-up motion by the visual image. The effectiveness of the proposed grasp selection is verified through some experiments with the universal robot hand. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CMCSN.2016.36 | 2016 Third International Conference on Computing Measurement Control and Sensor Network (CMCSN) |
Keywords | Field | DocType |
Robot Hand,Teleoperation,Visual Feedback,Tactile Feedback | Social robot,Computer vision,Robot control,Bang-bang robot,Computer science,Robot kinematics,Robot end effector,Artificial intelligence,Mobile robot navigation,Cartesian coordinate robot,Mobile robot | Conference |
ISBN | Citations | PageRank |
978-1-5090-1094-3 | 0 | 0.34 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Futoshi Kobayashi | 1 | 36 | 14.80 |
| Shou Minoura | 2 | 0 | 0.34 |
| Hiroyuki Nakamoto | 3 | 13 | 8.01 |
| Fumio Kojima | 4 | 77 | 18.33 |