A modular planar robotic manipulandum with end-point torque control

被引:171
作者
Howard, Ian S. [1 ]
Ingram, James N. [1 ]
Wolpert, Daniel M. [1 ]
机构
[1] Univ Cambridge, Dept Engn, Computat & Biol Learning Lab, Cambridge CB2 1PZ, England
基金
英国惠康基金;
关键词
vBOT; Robotic manipulandum; Motor learning; Torque; Stiffness; Object manipulation; Bimanual; INERTIA TENSOR; DYNAMIC TOUCH; MULTIJOINT MOVEMENT; ARM STIFFNESS; OBJECT; PERTURBATIONS; ORIENTATION; JOINT;
D O I
10.1016/j.jneumeth.2009.05.005
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Robotic manipulanda are extensively used in investigation of the motor control of human arm movements. They permit the application of translational forces to the arm based on its state and can be used to probe issues ranging from mechanisms of neural control to biomechanisms. However, most current designs are optimized for studying either motor learning or stiffness. Even fewer include end-point torque control which is important for the simulation of objects and the study of tool use. Here we describe a modular, general purpose, two-dimensional planar manipulandum (vBOT) primarily optimized for dynamic learning paradigms. It employs a carbon fibre arm arranged as a parallelogram which is driven by motors via timing pulleys. The design minimizes the intrinsic dynamics of the manipulandum without active compensation. A novel variant of the design (WristBOT) can apply torques at the handle using an add-on cable drive mechanism. In a second variant (StiffBOT) a more rigid arm can be substituted and zero cable drive mechanism. In a second variant (STiffBOT) a more rigid arm can be substituted ad zero backlash belts can be used, making the STiffBOT more suitable for the study of stiffness. The three variants can be used with custom built display rigs, mounting, and air tables. We investigated the performance of the vBOT and its variants in terms of effective end-point mass, viscosity and stiffness. Finally we present an object manipulation task using the WristBOT. This demonstrates that subjects can perceive the orientation of the principal axis of an object based on haptic feedback arising from its rotational dynamics. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:199 / 211
页数:13
相关论文
共 38 条
[1]   A robotic manipulator for the characterization of two-dimensional dynamic stiffness using stochastic displacement perturbations [J].
Acosta, AM ;
Kirsch, RF ;
Perreault, EJ .
JOURNAL OF NEUROSCIENCE METHODS, 2000, 102 (02) :177-186
[2]  
ADELSTEIN B, 1989, VIRTUAL ENV SYSTEM S
[3]   Flexible representations of dynamics are used in object manipulation [J].
Ahmed, Alaa A. ;
Wolpert, Daniel M. ;
Flanagan, J. Randall .
CURRENT BIOLOGY, 2008, 18 (10) :763-768
[4]   Weight perception and the haptic size weight illusion are functions of the inertia tensor [J].
Amazeen, EL ;
Turvey, MT .
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN PERCEPTION AND PERFORMANCE, 1996, 22 (01) :213-232
[5]  
[Anonymous], 1994, P ASME WINT ANN M S
[6]  
[Anonymous], 1966, The ecological approach to visual perception
[7]   Actions and consequences in bimanual interaction are represented in different coordinate systems [J].
Bays, Paul M. ;
Wolpert, Daniel M. .
JOURNAL OF NEUROSCIENCE, 2006, 26 (26) :7121-7126
[8]   The central nervous system stabilizes unstable dynamics by learning optimal impedance [J].
Burdet, E ;
Osu, R ;
Franklin, DW ;
Milner, TE ;
Kawato, M .
NATURE, 2001, 414 (6862) :446-449
[9]  
Charnnarong J., 1991, The design of an intelligent machine for upper-limb physical therapy
[10]   Learned dynamics of reaching movements generalize from dominant to nondominant arm [J].
Criscimagna-Hemminger, SE ;
Donchin, O ;
Gazzaniga, MS ;
Shadmehr, R .
JOURNAL OF NEUROPHYSIOLOGY, 2003, 89 (01) :168-176