TY - GEN
T1 - Tactile-based object center of mass exploration and discrimination
AU - Yao, Kunpeng
AU - Kaboli, Mohsen
AU - Cheng, Gordon
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/22
Y1 - 2017/12/22
N2 - In robotic tasks, object recognition and discrimination can be realized according to their physical properties, such as color, shape, stiffness, and surface textures. However, these external properties may fail if they are similar or even identical. In this case, internal properties of the objects can be considered, for example, the center of mass. Center of mass is an important inherent physical property of objects; however, due to the difficulties in its determination, it has never been applied in object discrimination tasks. In this work, we present a tactile-based approach to explore the center of mass of rigid objects and apply it in robotic object discrimination tasks. This work comprises three aspects: (a) continuous estimation of the target object's geometric information, (b) exploration of the center of mass, and (c) object discrimination based on the center of mass features. Experimental results show that by following our proposed approach, the center of mass of experimental objects can be accurately estimated, and objects of identical external properties but different mass distributions can be successfully discriminated. Our approach is also robust against the textural properties and stiffness of experimental objects.
AB - In robotic tasks, object recognition and discrimination can be realized according to their physical properties, such as color, shape, stiffness, and surface textures. However, these external properties may fail if they are similar or even identical. In this case, internal properties of the objects can be considered, for example, the center of mass. Center of mass is an important inherent physical property of objects; however, due to the difficulties in its determination, it has never been applied in object discrimination tasks. In this work, we present a tactile-based approach to explore the center of mass of rigid objects and apply it in robotic object discrimination tasks. This work comprises three aspects: (a) continuous estimation of the target object's geometric information, (b) exploration of the center of mass, and (c) object discrimination based on the center of mass features. Experimental results show that by following our proposed approach, the center of mass of experimental objects can be accurately estimated, and objects of identical external properties but different mass distributions can be successfully discriminated. Our approach is also robust against the textural properties and stiffness of experimental objects.
UR - http://www.scopus.com/inward/record.url?scp=85044444417&partnerID=8YFLogxK
U2 - 10.1109/HUMANOIDS.2017.8246975
DO - 10.1109/HUMANOIDS.2017.8246975
M3 - Conference contribution
AN - SCOPUS:85044444417
T3 - IEEE-RAS International Conference on Humanoid Robots
SP - 876
EP - 881
BT - 2017 IEEE-RAS 17th International Conference on Humanoid Robotics, Humanoids 2017
PB - IEEE Computer Society
T2 - 17th IEEE-RAS International Conference on Humanoid Robotics, Humanoids 2017
Y2 - 15 November 2017 through 17 November 2017
ER -