Backcasting: adaptive sampling for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Call and response: experiments in sampling the environment
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Contour estimation using collaborating mobile sensors
DIWANS '06 Proceedings of the 2006 workshop on Dependability issues in wireless ad hoc networks and sensor networks
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
ACE in the Hole: Adaptive Contour Estimation Using Collaborating Mobile Sensors
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Adaptive multi-robot wide-area exploration and mapping
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Efficient informative sensing using multiple robots
Journal of Artificial Intelligence Research
Multiscale sensing with stochastic modeling
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Compressive mobile sensing in robotic mapping
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Adaptive multiscale sampling in robotic sensor networks
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Active learning strategies: a case study for detection of emotions in speech
ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications
Level set estimation using uncoordinated mobile sensors
ADHOC-NOW'07 Proceedings of the 6th international conference on Ad-hoc, mobile and wireless networks
Tracking dynamic boundary fronts using range sensors
EWSN'08 Proceedings of the 5th European conference on Wireless sensor networks
Prioritized Sensor Detection for Environmental Mapping: Theory and Experiments
Journal of Intelligent and Robotic Systems
Accuracy-aware aquatic diffusion process profiling using robotic sensor networks
Proceedings of the 11th international conference on Information Processing in Sensor Networks
Pervasive and Mobile Computing
Active learning for level set estimation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper investigates data-adaptive path planning schemes for wireless networks of mobile sensor platforms. We focus on applications of environmental monitoring, in which the goal is to reconstruct a spatial map of environmental factors of interest. Traditional sampling theory deals with data collection processes that are completely independent of the target map to be estimated, aside from possible a priori specifications reflective of assumed properties of the target. We refer to such processes as passive learning methods. Alternatively, one can envision sequential, adaptive data collection procedures that use information gleaned from previous observations to guide the process. We refer to such feedback-driven processes as active learning methods. Active learning is naturally suited to mobile path planning, in which previous samples are used to guide the motion of the mobiles for further sampling. This paper presents some of the most encouraging theoretical results to date that support the effectiveness of active over passive learning, and focuses on new results regarding the capabilities of active learning methods for mobile sensing. Tradeoffs between latency, path lengths, and accuracy are carefully assessed using our theory. Adaptive path planning methods are developed to guide mobiles in order to focus attention in interesting regions of the sensing domain, thus conducting spatial surveys much more rapidly while maintaining the accuracy of the estimated map. The theory and methods are illustrated in the application of water current mapping in a freshwater lake.