Cooperative Target Tracking in a Distributed Autonomous Sensor Network

Abstract

Abstract-This paper describes an investigation into the control of multiple, cooperating autonomous sensor platforms operating in a marine sensor network. Distributed sensors allow us to view phenomena of interest from multiple, simultaneous vantage points, creating significant processing gain from the spatial diversity. The major objective of this paper is to describe a framework for adaptive and cooperative control of the autonomous sensor platforms in such a network. This framework has two major components, an intelligent sensor that provides highlevel state information to a behavior-based autonomous vehicle control system and a new approach to behavior-based control of autonomous vehicles using multiple objective functions that allows reactive control in complex environments with multiple constraints. Experimental results are presented for a 2-D target tracking application in which a pair of fully autonomous surface craft using simulated bearing sensors acquire and track a moving target. From these results, it is readily seen that there is the potential for potent synergy from the cooperation of multiple sensor platforms.

Adaptive autonomous underwater vehicles for littoral surveillance

“…Our collaborators at the Massachusetts Institute of Technology (MIT) have published about autonomous vehicles using passive sonar for ASW, for example on improving target tracking through bearing stabilization [36], and demonstrating a concept for multi-vehicle passive target tracking and classification using autonomous surface vehicles [14,15].…”

Refueling Strategies for a Team of Cooperating AUVs

“…Some protocols [8], focus on reliable communications while taking into consideration the energy demands of the acoustic modem, while others [9], [ 10] worry about packet loss and node hopping (sending a packet from source to destination via intermediary nodes). [11], [12], [13], [14], [15] specify the volatile nature of underwater communications, such as limited use of radio frequencies underwater (radio communications only work within the range of 30-300Hz and require large antennae and high transmission power [14]), loss of equipment due to the volatility of the ocean environment and changes in transmission speed of acoustic transmissions. [11] advocates the use of low-cost modems in underwater domains due to oceanic drift, battery replacement, and environmental damage.…”

“…A central management structure is not feasible in an underwater scenario due to intermittent communications [12], [13]. Each vehicle is not guaranteed to be close to, or have a signal strong enough to always receive information from a central database.…”

“…Each vehicle is not guaranteed to be close to, or have a signal strong enough to always receive information from a central database. [12], [13] point out the infeasibility of a centralized control scheme due to unreliability of underwater communications. These works focus on target tracking and show that a delay in communications between vehicles degrades the confidence of target tracking.…”

Information-theoretic integration of sensing and communication for active robot networks

“…The concept of using system inputs to improve the quality of information sensed by the system has been applied to a variety of problems. Example applications include: target tracking [2], [20], [21]; collaborative perception by unmanned ground and aerial vehicle teams [15]; vision-based navigation and control [22]; hierarchical reconnaissance by teams of unmanned aircraft [23] ; plume tracking by multiple autonomous underwater vehicles [5]; and cooperative radio source localization [24].…”