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This paper presents an algorithm for localizing an unmanned aerial vehicle (UAV) in GPS denied environments. Localization is performed with respect to a pre-built map of the environment represented using the distance function of a binary mosaic, avoiding the need for extraction and explicit matching of visual features. Edges extracted from images acquired by an on-board camera are projected to the...
The Electric Series Compliant Humanoid for Emergency Response (ESCHER) platform represents the culmination of four years of development at Virginia Tech to produce a full‐sized force‐controlled humanoid robot capable of operating in unstructured environments. ESCHER's locomotion capability was demonstrated at the DARPA Robotics Challenge (DRC) Finals when it successfully navigated the 61 m loose dirt...
The main contribution of this paper is an extended Kalman filter (EKF) based framework for mobile robot localisation in occupancy grid maps (OGMs), when the initial location is approximately known. We propose that the observation equation be formulated using the unsigned distance transform based Chamfer Distance (CD) that corresponds to a laser scan placed within the OGM, as a constraint. This formulation...
This paper presents a fast global scan matching technique for high-speed vehicle navigation. The proposed grid-based scan-to-map matching technique collectively handles unprocessed scan points at each grid cell as a grid feature. The grid features are transformed and located in the global frame and updated every time a new scan is acquired. Since registered and updated are only grid features, which...
Assistive Robotics(AR) is a rapidly expanding field, implementing advanced intelligent machines capable of working collaboratively with a range of human users; as assistants, tools and as companions. These AR devices can provide assistance to stretched carers when transferring non-ambulatory patients safely. This paper presents the preliminary outcomes of the design, development and implementation...
In this paper, the problem of localising a robot within a known two-dimensional environment is formulated as one of minimising the Chamfer Distance between the corresponding occupancy grid map and information gathered from a sensor such as a laser range finder. It is shown that this nonlinear optimisation problem can be solved efficiently and that the resulting localisation algorithm has a number...
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