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This thesis introduces the Information-rich Rapidly-exploring Random Tree (IRRT), an extension of the RRT algorithm that embeds information collection as predicted using Fisher information matrices. The primary contribution of this trajectory generation algorithm is target-based information maximization in general (possibly heavily constrained)(More)
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract— This paper describes the system architecture and core algorithms(More)
This paper presents vehicle models and test flight results for an autonomous fixed-wing aircraft with the capability to take off, hover, transition to and from level-flight, and perch on a vertical landing platform. These maneuvers are all demonstrated in the highly space constrained environment of the Real-time indoor Autonomous Vehicle test ENvironment(More)
This paper introduces the Information-rich Rapidly-exploring Random Tree (IRRT), an extension of the RRT algorithm that embeds information collection as predicted using Fisher Information Matrices. The primary contribution of this algorithm is target-based information maximization in general (possibly heavily constrained) environments, with complex vehicle(More)
— This paper considers the decision-making problem for a human-driven vehicle crossing a road intersection in the presence of other, potentially errant, drivers. Our approach relies on a novel threat assessment module, which combines an intention predictor based on support vector machines with an efficient threat assessor using rapidly-exploring random(More)
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract— This paper considers the path planning problem for an autonomous(More)
This paper considers the problem of online informative motion planning for a network of heterogeneous mobile sensing agents, each subject to dynamic constraints, environmental constraints, and sensor limitations. Previous work has not yielded algorithms that are amenable to such general constraint characterizations. In this paper, the information-rich(More)
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract We consider the sensor selection problem on multivariate Gaussian(More)
Proofs In order to prove Proposition 3, it is convenient to first prove the following lemma. Lemma A. Consider a connected GMRF G = (V, E; J) parameterized by precision matrix J and a unique path ¯ P embedded in G. The marginal precision matrix J ¯ P has block off-diagonal elements identical to those in the submatrix of J corresponding to variables in ¯ P ,(More)