Name
Abstract | ||
|---|---|---|
When designing new equipment for telecontrol, many experimental investigations are required. This increases time and cost of elaboration. The development of new design methods for telerobotic systems can help reduce the number of experimental investigations. For preliminary design of remote control systems these investigations may be replaced by modeling and simulation procedures. One promising method is based on a behavior study of the human operator (HO). A great number of studies use the speed-accuracy trade-off known as Fitts's law. This estimate and its modifications as applied to teleoperator design makes it possible to evaluate and predict the teleoperator performance. However, these results do not always permit sufficient evaluation of system quality; such evaluations are not quite precise and the resultant criterion dependences do not always correspond to the design problem of a concrete remote control system. Hence, profound studies of HO behavior can help simplify these procedures. The paper proposes a new methodology to evaluate and predict telerobot quality by means of a refined model of human behavior. The method was applied to investigate a new adaptive algorithm for telerobot operations. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/ROBOT.1997.614268 | ICRA |
Keywords | Field | DocType |
adaptive control,control system analysis,control system synthesis,human factors,position control,telerobotics,Fitts's law,adaptive algorithm,design methods,human motor behavior,human operator,refined model,remote control systems,speed-accuracy trade-off,teleoperator design,telerobot control,telerobot quality | Human operator,Remote control,Motor behavior,Control theory,Modeling and simulation,Control engineering,Design methods,Adaptive control,Engineering,Adaptive algorithm,Telerobotics | Conference |
Volume | Issue | ISSN |
2 | 1 | 1050-4729 |
Citations | PageRank | References |
1 | 0.38 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leonid Slutski | 1 | 4 | 2.31 |
| Irina Gurevich | 2 | 1 | 0.38 |
| Yael Edan | 3 | 514 | 53.29 |