This paper describes a controller design method for robots supporting human in real environment. Such robots have to cope with various interactions between robots and human environment. Furthermore, they also have to autonomously classify the interaction from sensor information and select their action according to tasks and situations. This study introduces an idea of spatial filter to construct such a control system. Spatial filter is based on the idea of functionality. The idea is to decompose a large-scale control system into units called “function”. A function corresponds to an action of the control system such as “grasping”, “moving” and so on. A complicated task is achieved by superpositioning multiple functions. To construct function-based controllers, the arm coordinate space is transformed into a new coordinate space based on function modes. Fig. 1 shows composition of spatial filter. Spatial filter is an idea that treats a motion control system as a kind of a filter. It gathers information from spatially-arranged sensors. The sensor information is decomposed into function modes by a coordinate transformation matrix. Controller composition is determined based on a filter characteristic on each mode. A controller with force feedback passes force while a controller without force feedback cuts it. Controllers give input to the robot through inverse modal decomposition. Position response of the robot depends on force input from human and characteristic of spatial filter. Fig. 2 shows the overview of an experiment with spatial filter. The experimental system is composed of 3 twin-drive parallel-link manipulators. Table 1 shows functions applied then. SC, RC, GR and VC denote spring coupling, rigid coupling, grasping and velocity control function, respectively. When the operator maneuvered one of the manipulators in Step 1, all three manipulators moved only in grasping mode and accomplished open-close motion. An object was grasped in Step 2 after the operator inserted it. The object was tilted in the pitching mode in Step 3 when the operator applied force in the z direction. On the other hand, the object went up and down in Step 4 when the operator applied force in the same direction. The robot was always obedient to the operator on the mode with spring coupling function, the function with force control. On the other hand, the robot kept constant position on the mode with rigid coupling function. Rigid coupling
[1]
Tsuneo Yoshikawa,et al.
Manipulating and grasping forces in manipulation by multifingered robot hands
,
1987,
IEEE Trans. Robotics Autom..
[2]
Kouhei Ohnishi,et al.
Motion Control Taking Environmental Information into Account
,
2002
.
[3]
Kouhei Ohnishi,et al.
A Design of Decentralized Control System in Unstrnctured Environment
,
2003
.
[4]
Kouhei Ohnishi,et al.
Contact motion in unknown environment
,
2003,
IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468).
[5]
Kouhei Ohnishi,et al.
An architecture of decentralized control for multi-degrees of freedom parallel manipulator
,
2002,
7th International Workshop on Advanced Motion Control. Proceedings (Cat. No.02TH8623).
[6]
Kouhei Ohnishi,et al.
Quarry of Modal Information from Environment for Advanced Motion Control
,
2006
.
[7]
K. Ohnishi,et al.
An extraction method of environmental surface profile using planar end-effectors
,
2006,
9th IEEE International Workshop on Advanced Motion Control, 2006..
[8]
Toshiyuki Murakami,et al.
Force Sensorless Compliant Control Based on Reaction Force Estiation Observer in Multi-Degrees-of-Freedom Robot
,
1993
.
[9]
A.G. Loukianov,et al.
Observer based decomposition control of linear delayed systems
,
2001,
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).
[10]
Kouhei Ohnishi,et al.
A controller design method based on functionality
,
2006,
AMC 2006.
[11]
Suguru Arimoto,et al.
Principle of Superposition for Realizing Dexterous Pinching Motions of a Pair of Robot Fingers with Soft-Tips
,
2001
.
[12]
Kouhei Ohnishi,et al.
A Controller Design Method of Decentralized Control System
,
2006
.
[13]
Yoshihiko Nakamura,et al.
Polynomial design of the nonlinear dynamics for the brain-like information processing of whole body motion
,
2002,
Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).