Fast minimum uncertainty search on a graph map representation

Carrillo, Henry; Latif, Yasir; Neira, José; Castellanos, José A.

doi:10.1109/iros.2012.6385927

Cited by 15 publications

(7 citation statements)

References 28 publications

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“…They also agree with previous works in active calibration such as [8], which reports from a theoretical perspective that determinant based criteria are the best choice for precise calibration. Also, in a loosely related field of research, such as SLAM [11], [21], the same behavior have been previously reported.…”

Section: A Greedy Optimization and Active Robot Calibrationsupporting

confidence: 83%

On task-oriented criteria for configurations selection in robot calibration

Carrillo

Birbach

Täubig

et al. 2013

2013 IEEE International Conference on Robotics and Automation

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This paper studies different criteria for selecting configurations for the task of calibrating a robotic system. Given an automatic and self-contained procedure which allows the robot to calibrate itself without the need of external tools, we are interested in how to select the set of configurations that maximize calibration accuracy while minimizing calibration time. We experiment with the active calibration of a multi sensorial humanoid's upper body and report that determinant based criteria should be preferred when a greedy selection is used. In addition to criteria comparison, we further propose a new criterion for configuration selection. Its novelty stems from a direct treatment of the robot's end-effector tool variance. This is contrary to previous approaches which target the variance indirectly via calibration parameters. Our proposed objective function is derived as a compact formulation from the mean error of the robot's end-effector tool from which its variance can be computed using traditional criteria known from the theory of optimal experimental design (e.g. A-optimality).

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Section: A Greedy Optimization and Active Robot Calibrationsupporting

confidence: 83%

On task-oriented criteria for configurations selection in robot calibration

Carrillo

Birbach

Täubig

et al. 2013

2013 IEEE International Conference on Robotics and Automation

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“…Some planners seek to maximize the probability of success or rather to minimize an expected cost by taking into account the sensing uncertainty (Carrillo et al., ; Gonzalez & Stentz, ; Pepy & Lambert, ; Platt et al., ; Prentice & Roy, ; van den Berg, Abbeel, & Goldberg, ) while other path planners focus on generating paths with minimum probability of collision with obstacles (Blackmore, Ono, & Williams, ; Burns & Brock, ; Guibas et al., ; Missiuro & Roy, ; Nakhaei & Lamiraux, ).…”

Section: Related Workmentioning

confidence: 99%

Coverage Path Planning with Real-time Replanning and Surface Reconstruction for Inspection of Three-dimensional Underwater Structures using Autonomous Underwater Vehicles

et al. 2014

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We present a novel method for planning coverage paths for inspecting complex structures on the ocean floor using an autonomous underwater vehicle (AUV). Our method initially uses a 2.5-dimensional (2.5D) prior bathymetric map to plan a nominal coverage path that allows the AUV to pass its sensors over all points on the target area. The nominal path uses a standard mowing-the-lawn pattern in effectively planar regions, while in regions with substantial 3D relief it follows horizontal contours of the terrain at a given offset distance. We then go beyond previous approaches in the literature by considering the vehicle's state uncertainty rather than relying on the unrealistic assumption of an idealized path execution. Toward that end, we present a replanning algorithm based on a stochastic trajectory optimization that reshapes the nominal path to cope with the actual target structure perceived in situ. The replanning algorithm runs onboard the AUV in real time during the inspection mission, adapting the path according to the measurements provided by the vehicle's range-sensing sonars. Furthermore, we propose a pipeline of state-of-the-art surface reconstruction techniques we apply to the data acquired by the AUV to obtain 3D models of the inspected structures that show the benefits of our planning method for 3D mapping. We demonstrate the efficacy of our method in experiments at sea using the GIRONA 500 AUV, where we cover part of a breakwater structure in a harbor and an underwater boulder rising from 40 m up to 27 m depthThis research has been sponsored by the Government of Spain (COMAROB Project, DPI2011-27977-C03-02), the MORPH EU FP7-Project (grant agreement FP7-ICT-2011-7-288704), and the Eurofleets2 EU FP7-Project (grant agreement FP7-INF-2012-312762). The authors are grateful to Lluis Magi, Carles Candela, and Arnau Carrera for helping with the GIRONA 500 operation

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“…While the smaller database gives a noisier result, the underlying network structure is still distinctly visible, and the vehicle state knowledge is likely sufficient to carry out basic navigational tasks. For example, by inferring path crossings as intersections, uncertaintycognizant pose-graph-based path planners, such as [29]- [31], could be used to plan routes within such a reduced graph.…”

Section: B Location Utility-based Map Reductionmentioning

confidence: 99%

Location utility-based map reduction

Steiner¹,

Huang

Leonard³

2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-Maps used for navigation often include a database of location descriptions for place recognition (loop closing), which permits bounded-error performance. A standard posegraph SLAM system adds a new entry for every new pose into the location database, which grows linearly and unbounded in time and thus becomes unsustainable. To address this issue, in this paper we propose a new map-reduction approach that pre-constructs a fixed-size place-recognition database amenable to the limited storage and processing resources of the vehicle by exploiting the high-level structure of the environment as well as the vehicle motion. In particular, we introduce the concept of location utility -which encapsulates the visitation probability of a location and its spatial distribution relative to nearby locations in the database -as a measure of the value of potential loop-closure events to occur at that location. While finding the optimal reduced location database is NPhard, we develop an efficient greedy algorithm to sort all the locations in a map based on their relative utility without access to sensor measurements or the vehicle trajectory. This enables pre-determination of a generic, limited-size place-recognition database containing the N best locations in the environment. To validate the proposed approach, we develop an open-source street-map simulator using real city-map data and show that an accurate map (pose-graph) can be attained even when using a place-recognition database with only 1% of the entries of the corresponding full database.

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Fast minimum uncertainty search on a graph map representation

Cited by 15 publications

References 28 publications

On task-oriented criteria for configurations selection in robot calibration

On task-oriented criteria for configurations selection in robot calibration

Coverage Path Planning with Real-time Replanning and Surface Reconstruction for Inspection of Three-dimensional Underwater Structures using Autonomous Underwater Vehicles

Location utility-based map reduction

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