Tactile sensing has been used in robotics for object identification, grasping, and material recognition. Most material recognition approaches use vibration signals from a tactile exploration, typically above one second long, to identify the material. This work proposes a tactile multi-modal (vibration and thermal) material identification approach based on recursive Bayesian estimation. Through the frequency response of the vibration induced by the material and thermal features, like an estimate of the thermal power loss of the finger, we show that it is possible to identify materials in less than half a second. Moreover, a comparison between vibration only and multi-modal identification shows that both recognition time and classification errors are reduced by adding thermal information.
|Title of host publication||2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)|
|Publication status||Published - 2016|
|Event||2016 IEEE/RSJ International Conference on Intelligent Robots and Systems - Daejeon, Korea, Republic of|
Duration: 9. Oct 2016 → 14. Oct 2016
|Conference||2016 IEEE/RSJ International Conference on Intelligent Robots and Systems|
|Country||Korea, Republic of|
|Period||09/10/2016 → 14/10/2016|