Danelle C. Shah

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This paper introduces a novel planning and estimation framework for maximizing information collection in missions involving cooperative teams of multiple autonomous vehicles and human agents, such as those used for multi-target search and tracking. The main contribution of this work is the scalable unification of effective algorithms for distributed(More)
In this paper, scalable collaborative human-robot systems for information gathering applications are approached as a decentralized Bayesian sensor network problem. Human-computer augmented nodes and autonomous mobile sensor platforms are collaborating on a peer-to-peer basis by sharing information via wireless communication network. For each node, a(More)
A fully probabilistic command interface for controlling robots using multi-stroke sketch commands is presented. Drawing from prior work in handwriting recognition, sketches are modeled as a variable duration hidden Markov model, where the distributions on the states and transitions are learned from training data. A forward search algorithm on the gesture,(More)
A novel method for controlling a mobile robot using qualitative inputs in the context of an approximate map, such as one sketched by a human, is presented. By defining a desired trajectory with respect to observable landmarks, human operators can send semi-autonomous robots into areas for which a truth map is not available. Waypoint planning is formulated(More)
In order to save numerous man power hours fritter away to monitor various process parameters in industries whole day, the design presented in this paper gives solution to acquire data at desired rate and monitor fault with alarm system. The design introduces wireless information flow between on field acquisition and remote monitoring part at the office. D(More)
Network science is often used to understand underlying phenomena that are reflected through data. In real-world applications, this understanding supports decision makers attempting to solve complex problems. Practitioners designing such systems must overcome difficulties due to the practical limitations of the data and the fidelity of a network abstraction.(More)
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. This paper introduces a novel planning and estimation framework for maximizing information collection in missions involving cooperative teams of multiple autonomous vehicles and human agents, such as those used for multi-target search and(More)