Sensor allocation for behavioral sensor fusion using min-conflict with happiness

For mobile robots employing reactive behaviors, allocation of physical sensors to satisfy sensing needs should be dynamic and fast. It is becoming increasingly apparent that this allocation should also support behavioral sensor fusion, as indicated by experimental data, in order to maximize the use of available sensing hardware and to increase the quality of sensing. These issues are addressed in the context of the min-conflict with happiness algorithm for dynamic sensor allocation, whose execution rates on two real robots ranged from 11 to 17 milliseconds. Experimental results are shown which illustrate the improvements (27.5%-75% of observations) achieved using sensor fusion. The paper also contributes a quantitative representation of sensing quality using t-norms, allowing fused sensors to be compared with single sensors for a behavior