Multisensor fusion in Reconfigurable Robots using Adaptive Transformation

Author(s):  
A.P. Povendhan ◽  
A. A. Hayat ◽  
Lim Yi ◽  
J. C. C. Hoong ◽  
M. R. Elara
2000 ◽  
Author(s):  
Laura D. Vann ◽  
Kevin M. Cuomo ◽  
Jean E. Piou ◽  
Joseph T. Mayhan

Author(s):  
Guimin Chen ◽  
Yanjie Gou ◽  
Aimei Zhang

A compliant multistable mechanism is capable of steadily staying at multiple distinct positions without power input. Many applications including switches, valves, relays, positioners, and reconfigurable robots may benefit from multistability. In this paper, two new approaches for synthesizing compliant multistable mechanisms are proposed, which enable designers to achieve multistability through the use of a single bistable mechanism. The synthesis approaches are described and illustrated by several design examples. Compound use of both approaches is also discussed. The design potential of the synthesis approaches is demonstrated by the successful operation of several instantiations of designs that exhibit three, four, five, and nine stable equilibrium positions, respectively. The synthesis approaches enable us to design a compliant mechanism with a desired number of stable positions.


2015 ◽  
Vol 764-765 ◽  
pp. 1319-1323
Author(s):  
Rong Shue Hsiao ◽  
Ding Bing Lin ◽  
Hsin Piao Lin ◽  
Jin Wang Zhou

Pyroelectric infrared (PIR) sensors can detect the presence of human without the need to carry any device, which are widely used for human presence detection in home/office automation systems in order to improve energy efficiency. However, PIR detection is based on the movement of occupants. For occupancy detection, PIR sensors have inherent limitation when occupants remain relatively still. Multisensor fusion technology takes advantage of redundant, complementary, or more timely information from different modal sensors, which is considered an effective approach for solving the uncertainty and unreliability problems of sensing. In this paper, we proposed a simple multimodal sensor fusion algorithm, which is very suitable to be manipulated by the sensor nodes of wireless sensor networks. The inference algorithm was evaluated for the sensor detection accuracy and compared to the multisensor fusion using dynamic Bayesian networks. The experimental results showed that a detection accuracy of 97% in room occupancy can be achieved. The accuracy of occupancy detection is very close to that of the dynamic Bayesian networks.


2003 ◽  
Vol 44 (3-4) ◽  
pp. 191-199 ◽  
Author(s):  
K. Støy ◽  
W.-M. Shen ◽  
P.M. Will

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