MAS 0: Multi-scale Actuation and Sensing: An Overview

Center for Embedded Networked Sensing Multiscale Actuation and Sensing: Overview Bill Kaiser, Mark Hansen, Gaurav Sukhatme and the MAS Team Controlled Mobility, Adaptive Sampling, NIMS and NAMOS • Controlled mobility may reduce the energy cost of data transport in wireless sensor networks • Multiscale methods can exploit sparsely deployed low resolution sensors to both extract models of observed phenomena and detect events that guide actuated sensors to best sample dynamically varying fields. • Development of aquatic sensing systems (NAMOS lake monitoring) and NIMS (aquatic stream, river, and lake systems as well as many terrestrial ecosystems). NIMS: Networked Infomechanical System • Multiscale Sensing: – Hierarchy of sensor data sources – Varying levels of resolution – Achieve high fidelity by multiple levels of sparse sensing • Model Based Methods: – Directly extract phenomena behavior – Communication, computation, and actuation optimized for highest utility sensing operations – Continuous model update MAS Theory Medium Characteristics, H Belief about Phenomenon, I Current Configuration, X Difference Architecture and Performance Distributed Actuation Algorithm dx=f(H,X,I,C) dx, small actuation command Motion Actuators Pan, Zoom, Tilt Camera Actuated Laser Range Sensor Background Ignore Small Blobs Filter by Aspect ratio Events 5000 events collected Coordinated Actuation for Environment Observation NAMOS: Networked Aquatic Microbial Observing System UCLA – UCR – Caltech – USC – CSU – JPL – UC Merced