NDLI: A graph traversal based algorithm for obstacle detection using lidar or stereo

Content Provider	IEEE Xplore Digital Library
Author	Kuthirummal, Sujit Das, Aveek Samarasekera, Supun
Copyright Year	2011
Description	Author affiliation: Vision and Robotics Lab, SRI International, Sarnoff, Princeton, NJ, USA (Kuthirummal, Sujit; Das, Aveek; Samarasekera, Supun)
Abstract	We present a novel computationally efficient approach to obstacle detection that is applicable to both structured (e.g. indoor, road) and unstructured (e.g. off-road, grassy terrain) environments. In contrast to previous works that attempt to explicitly identify obstacles, we explicitly detect scene regions that are traversable - safe for the robot to go to - from its current position. Traversability is defined on a 2D grid of cells. Given 3D points, we map them to individual cells and compute histograms of elevations of the points in each cell. This elevation information is then used in a graph based algorithm to label all traversable cells. In this manner, positive and negative obstacles, as well as unknown regions are implicitly detected and avoided. Our notion of traversability does not make any flat-world assumptions and does not need sensor pitch-roll compensation. It also accounts for overhanging structures like tree branches. We demonstrate that our approach can be used with both lidar and stereo sensors even though the two sensors differ in their resolution and accuracy. We present several results from our real-time implementation on realistic environments using both lidar and stereo.
Starting Page	3874
Ending Page	3880
File Size	1481410
Page Count	7
File Format	PDF
ISBN	9781612844541
ISSN	21530858
e-ISBN	9781612844565
DOI	10.1109/IROS.2011.6094685
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three dimensional displays Laser radar Histograms Robot kinematics Robot sensing systems Cameras
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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