scholarly journals Bio-mimetic impedance control of robotic manipulator for dynamic contact tasks

2008 ◽  
Vol 56 (4) ◽  
pp. 306-316 ◽  
Author(s):  
Toshio Tsuji ◽  
Yoshiyuki Tanaka
Author(s):  
Adam Pettinger ◽  
Mitch Pryor

Abstract In this paper we introduce the Generalized Contact Control Framework (GCCF) implemented on a compliant robotic manipulator. We demonstrate that the combined joint compliance and GCCF-based compliance control enable the completion of complex contact tasks in uncertain environments, where complex refers to the need to meet different contact force requirements involving multiple steps and output axes. Operating in uncertain environments means limited knowledge of the location or material properties of contact objects. The demonstrated tasks include opening a pill bottle and rigidly connecting to a purely mechanical tool changer. The GCCF simplifies the definition and modification of contact control parameters and allows for on-the-fly definition and completion of new tasks. Unlike hybrid force/impedance controllers, we do not need to define large damping and stiffness matrices, and we decouple the joint level control gains from the compliance control. The result is a robotic manipulator that can dynamically switch between unconstrained motion and contact tasks and provides a lot of versatility to perform a wide variety of tasks.


2007 ◽  
Vol 19 (1) ◽  
pp. 106-113
Author(s):  
Mutsuhiro Terauchi ◽  
◽  
Yoshiyuki Tanaka ◽  
Seishiro Sakaguchi ◽  
Nan Bu ◽  
...  

Impedance control is one of the most effective control methods for interaction between a robotic manipulator and its environment. Robot impedance control regulates the response of the manipulator to contact and virtual impedance control regulates the manipulator's response before contact. Although these impedance parameters may be regulated using neural networks, conventional methods do not consider regulating robot impedance and virtual impedance simultaneously. This paper proposes a simultaneous learning method to regulate the impedance parameters using neural networks. The validity of the proposed method is demonstrated in computer simulations of tasks by a multi-joint robotic manipulator.


Author(s):  
Youssef Michel ◽  
Rahaf Rahal ◽  
Claudio Pacchierotti ◽  
Paolo Robuffo Giordano ◽  
Dongheui Lee

Sign in / Sign up

Export Citation Format

Share Document