Name
Abstract | ||
|---|---|---|
Touch is an important sensory pathway for exploring the world, but most robotic systems either have no sense of touch, use simple binary bump switches, or require expensive custom sensors. In this work we investigate the use of low-cost sensors to acquire more discriminative representations of touch sensations. We show that using two pressure sensors in a 3D-printed housing we can determine the location of a touch along a one dimensional axis. Furthermore, we can distinguish between different types of touches by the profile of the sensor response. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICARA.2015.7081160 | ICARA |
Keywords | Field | DocType |
tactile sensors,force | Computer vision,Robotic systems,Computer science,Pressure sensor,Artificial intelligence,Sensory system,Discriminative model,Grippers,Tactile sensor | Conference |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrien Jule | 1 | 0 | 0.34 |
| brendan mccane | 2 | 223 | 33.05 |
| Alistair Knott | 3 | 315 | 61.10 |
| Steven Mills | 4 | 41 | 17.74 |