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Midway through the 2007 DARPA Urban Challenge, MIT's autonomous Land Rover LR3 'Talos' and Team Cornell's autonomous Chevrolet Tahoe 'Skynet' collided in a low-speed accident, one of the first well-documented collisions between two full-size autonomous vehicles. This collaborative study between MIT and Cor-nell examines the root causes of the collision,(More)
Team Cornell's Skynet is an autonomous Chevrolet Tahoe built to compete in the 2007 DARPA Urban Challenge. Skynet consists of many unique subsystems, including actua-tion and power distribution designed in-house, a tightly coupled attitude and position es-timator, a novel obstacle detection and tracking system, a system for augmenting position estimates(More)
Multiple, highly autonomous, satellite systems are envisioned in the near future because they are capable of higher performance, lower cost, better fault tolerance, reconfigurability and upgradability. This paper presents an architecture and multi-agent design and simulation environment that will enable agent-based multi-satellite systems to fulfill their(More)
A novel-tracking algorithm is presented as a computationally feasible, real-time solution to the joint estimation problem of data assignment and dynamic obstacle tracking from a potentially moving robotic platform. The algorithm implements a Rao-Blackwellized particle filter (RBPF) to factorize the joint estimation problem into 1) a data assignment problem(More)
In this paper, an algorithm to segment 3D points in dense range maps generated from the fusion of a single optical camera and a multiple emitter/detector laser range finder is presented. The camera image and laser range data are fused using a Markov Random Field to estimate a 3D point corresponding to each image pixel. The textured 3D dense point cloud is(More)
—This paper considers the distributed data fusion (DDF) problem for general multi-agent robotic sensor networks in applications such as 3D mapping and target search. In particular, this paper focuses on the use of conservative fusion via the weighted exponential product (WEP) rule to combat inconsistencies that arise from double-counting common information(More)
A general method for mapping dynamic environments using a Rao-Blackwellized particle filter is presented. The algorithm rigorously addresses both data association and target tracking in a single unified estimator. The algorithm relies on a Bayesian factorization to separate the posterior into: 1) a data association problem solved via particle filter; and 2)(More)
This paper presents a novel optimization-based path planner that is capable of planning multiple contingency paths to directly account for uncertainties in the future trajectories of dynamic obstacles. This planner addresses the particular problem of probabilistic collision avoidance for autonomous road vehicles that are required to safely interact, in(More)
A new method is presented for fusing conventional continuous sensor observations with discrete multi-categorical state-dependent information, which can be furnished by humans in many cooperative human-robot interaction problems. The hybrid likelihood function for mapping between continuous hidden states and categorical observations are specified via softmax(More)