Grip Control Using Biomimetic Tactile Sensing Systems

• Published in: IEEE/ASME transactions on mechatronics Vol. 14; no. 6; pp. 718 - 723
• Main Authors: Wettels, N., Parnandi, A.R., Ji-Hyun Moon, Loeb, G.E., Sukhatme, G.S.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-12-2009; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Anthropomorphism; Bayesian methods; Biomimetic; Biomimetics; Biosensors; Control systems; Detection; dexterous manipulators; Force sensors; grip control; Inference algorithms; Mathematical analysis; Mechatronics; On-line systems; Prosthetic hand; Prosthetics; Sensors; Tactile; tactile sensor; Tactile sensors
• ISSN: 1083-4435; 1941-014X
• DOI: 10.1109/TMECH.2009.2032686

We present a proof-of-concept for controlling the grasp of an anthropomorphic mechatronic prosthetic hand by using a biomimetic tactile sensor, Bayesian inference, and simple algorithms for estimation and control. The sensor takes advantage of its compliant mechanics to provide a triaxial force sensing end-effector for grasp control. By calculating normal and shear forces at the fingertip, the prosthetic hand is able to maintain perturbed objects within the force cone to prevent slip. A Kalman filter is used as a noise-robust method to calculate tangential forces. Biologically inspired algorithms and heuristics are presented that can be implemented online to support rapid, reflexive adjustments of grip.