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The problem of modeling and predicting spa-tiotemporal traffic phenomena over an urban road network is important to many traffic applications such as detecting and forecasting congestion hotspots. This paper presents a decentralized data fusion and active sensing (D 2 FAS) algorithm for mobile sensors to actively explore the road network to gather and(More)
The exploration problem is a central issue in mobile robotics. A complete terrain coverage is not practical if the environment is large with only a few small hotspots. This paper presents an adaptive multi-robot exploration strategy that is novel in performing both wide-area coverage and hotspot sampling using non-myopic path planning. As a result, the(More)
This paper presents a task allocation scheme via self-organizing swarm coalitions for distributed mobile sensor network coverage. Our approach uses the concepts of ant behavior to self-regulate the regional distributions of sensors in proportion to that of the moving targets to be tracked in a non-stationary environment. As a result , the adverse effects of(More)
A central problem in environmental sensing and monitoring is to classify/label the hotspots in a large-scale environmental field. This paper presents a novel decentralized active robotic exploration (DARE) strategy for probabilis-tic classification/labeling of hotspots in a Gaussian process (GP)-based field. In contrast to existing state-of-the-art(More)
Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth's climate and ecology. Typical ocean sensing is done with satellites or in situ buoys and research ships which are slow to reposition. Cloud cover inhibits study of localized transient phenomena such as Harmful Algal Blooms (HAB). A fleet of(More)
A key challenge of environmental sensing and monitoring is that of sensing, modeling, and predicting large-scale, spatially correlated environmental phenomena, especially when they are unknown and non-stationary. This paper presents a decentralized multi-robot active sensing (DEC-MAS) algorithm that can efficiently coordinate the exploration of multiple(More)
Central to robot exploration and mapping is the task of persistent localization in environmental fields characterized by spatially correlated measurements. This paper presents a Gaus-sian process localization (GP-Localize) algorithm that, in contrast to existing works, can exploit the spatially correlated field measurements taken during a robot's(More)
A key challenge in non-cooperative multi-agent systems is that of developing efficient planning algorithms for intelligent agents to interact and perform effectively among boundedly rational, self-interested agents (e.g., humans). The practicality of existing works addressing this challenge is being undermined due to either the restrictive assumptions of(More)
— The work in this paper describes a distributed layered architecture for resource-constrained multi-robot cooperation , which is utilized in autonomic mobile sensor network coverage. In the upper layer, a dynamic task allocation scheme self-organizes the robot coalitions to track efficiently across regions. It uses concepts of ant behavior to self-regulate(More)