Abstract This paper adopts the concept of random weighting estimation to multi-sensor data fusion. It presents a new random weighting estimation methodology for optimal fusion of multi-dimensional position data. A multi-sensor observation model is constructed for multi-dimensional position. Based on this observation model, a random weighting estimation algorithm is developed to estimate positio...

Social systems are calling attention to adequate sets of rules as e.g. to comply with the rules of Asimov as a codex [BF05]. In the context of Multiple Sensor Data Fusion (MSDF) a variety of interacting (logical) sensor agents might autonomously self-organize their part of complex tasks’ organizational solution processes due to co-operations, communications and co-ordinations. Even computationa...

  Omni directional mobile robots have been popularly employed in several applications especially in soccer player robots considered in Robocup competitions. However, Omni directional navigation system, Omni-vision system and solenoid kicking mechanism in such mobile robots have not ever been combined. This situation brings the idea of a robot with no head direction into existence, a comprehensi...

Multi sensor systems have performances that depend on the type of multi sensor data fusion. Multi sensor data fusion of raw detections (plots) has high performances but is seldom used in operational applications. A less efficient data fusion is preferred in the majority of operational multi sensor systems: data fusion of sensor tracks. Data fusion of sensor tracks is simpler and requires limite...

Because of the sensor or environment problem, the multi-sensor detection data can result in data mutation for the individual sensor. To obtain consistent, stable and accurate tested target description, the paper adopts confidence distance matrix, distance correlation coefficient and p-value significant test to get The number of optimal fusion number of multi-sensor, and uses maximum likelihood ...