Information-Theoretic Motion Planning for Constrained Sensor Networks

This paper considers the problem of online informative motion planning for a network of heterogeneous sensing agents, each subject to dynamic constraints, environmental constraints, and sensor limitations. Prior work has not yielded algorithms that are amenable to such general constraint characterizations. In this paper, we propose the Information-rich Rapidly-exploring Random Tree (IRRT) algorithm as a solution to the constrained informative motion planning problem that embeds metrics on uncertainty reduction at both the tree growth and path selection levels. IRRT possesses a number of beneficial properties, chief among them being the ability to find dynamically feasible, informative paths on short timescales, even subject to the aforementioned constraints. The utility of IRRT in efficiently localizing stationary targets is demonstrated in a progression of simulation results with both single-agent and multiagent networks. These results show that IRRT can be used in real-time to generate and execute information-rich paths in tightly constrained environments.AFOSR and USAF under grant (FA9550-08-1-0086

Integrated Relative-Measurement-Based Network Localization and Formation Maneuver Control (Extended Version)

This paper studies the problem of integrated distributed network localization and formation maneuver control. We develop an integrated relative-measurement-based scheme, which only uses relative positions, distances, bearings, angles, ratio-of-distances, or their combination to achieve distributed network localization and formation maneuver control in $\mathbb{R}^d (d \ge 2)$. By exploring the localizability and invariance of the target formation, the scale, rotation, and translation of the formation can be controlled simultaneously by only tuning the leaders' positions, i.e., the followers do not need to know parameters of the scale, rotation, and translation of the target formation. The proposed method can globally drive the formation errors to zero in finite time over multi-layer $d\!+\!1$-rooted graphs. A simulation example is given to illustrate the theoretical results.Comment: 12 pages; 7 figures, title corrected, DOI adde

Adaptive Distributed Resource Allocation in Wireless Sensor Networks

Wireless sensor networks have emerged as a promising technology for a wide range of important applications. A major research challenge in this field is the distributed resource allocation problem, which concerns how the limited resources in a wireless sensor network should be allocated or scheduled to minimize costs and maximize the network capability. In this paper, we propose the Adaptive Distributed Resource Allocation (ADRA) scheme, an adaptive approach for distributed resource allocation in wireless sensor networks. Our scheme specifies relatively simple local actions to be performed by individual sensor nodes in a wireless sensor network for mode management. Each node adapts its operation over time in response to the status and feedback of its neighboring nodes. Desirable global behavior results from the local interactions between nodes. We study the effectiveness of the ADRA scheme for a realistic application scenario; namely, the sensor mode management in an acoustic sensor network to track vehicle movement. We evaluated the scheme via simulations, and also prototyped it using the Crossbow MICA2 motes. Our simulation and hardware implementation results indicate that the ADRA scheme provides a good tradeoff between performance objectives such as coverage area, power consumption, and network lifetime.Singapore-MIT Alliance (SMA

Robot and Sensor Networks for First Responders

A network of distributed mobile sensor systems can help first responders during emergencies. Experiments conducted at a burning building with firefighters show the sensors’ potential to localize themselves and acquire and combine information, providing an integrative view of a dynamically changing environment

Bearing angle based cooperative source localization

© 2014 IEEE. This paper deals with the cooperative source localization problem with the goal of having an accurate estimate of the coordinate of the source cooperatively by a group of unicycle-type mobile agents. Neither absolute positioning information nor a common sense of direction is shared by the agents. Each agent gets its estimate about the source's coordinate in its own local frame based on the bearing measurements about its neighbors (that may or may not include the source) together with its own linear and angular speed information. A continuous time estimation scheme and a distributed fusion scheme are proposed for this goal such that the source's relative coordinate can be estimated at any time by each agent no matter whether it can directly detect the source or not. The globally asymptotic convergence of the estimation scheme and the fusion scheme is rigorously analyzed. Simulation results are also provided to verify the effectiveness of the proposed algorithms