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University of Waterloo

1. Skikos, Benjamin Anargyros Peregrine. LIDAR Odometry with Joint Geometric and Appearance Landmarks.

Degree: 2019, University of Waterloo

Odometry is the problem of estimating the motion of a moving platform relative to its environment without measurements to a fixed reference point. This is a critical problem for mobile robotics applications where measurements to a fixed reference point are not always assured, such as self-driving cars operating in GPS-denied environments and with physical landmarks potentially obscured by other traffic. Even when a fixed reference is available, motion estimates still improve position estimates by constraining the change in position over short timescales. A fundamental limitation of odometry is that assuming some non-zero error, the path produced by integrating odometry will always diverge from the true path. The rate of divergence depends on the ego-motion and the environment. Aggressive motions such as rapid rotation or high acceleration are likely to cause greater error because they are more difficult to model compared to more sedate motions. Odometry that functions by comparing consecutive sensor samples to determine motion can exhibit greater drift due to high velocity because high velocity reduces the overlap between sensor samples. Lastly, unstructured portions of the scene may not contain useful information to fully constrain the ego-motion. A good example is moving next to a flat featureless wall since observations of that wall only constrain perpendicular motion. In mobile robotics, both camera and lidar are commonly used for odometry. Lidar is a sensor technology that measures the time of flight of laser pulses to collect range-bearing samples from the scene. Lidars are used instead of cameras for certain applications despite their relatively high cost because lidars are not affected by ambient lighting conditions; they do not suffer from glare, or have to trade-off motion blur and sensitivity in low- light conditions. An ancillary benefit of using lidar is that the direct range measurement capability of lidar removes complexity from the odometry algorithm because the distance of sampled points does not have to be estimated from multiple sensor measurements. Lidar odometry algorithms already exist yet there are opportunities for improvement. The intensity information collected by lidar commonly goes unused, with few of the top- performing lidar odometry algorithms on the Kitti odometry dataset leveraging it. As- suming that scenes lacking both geometric and appearance information are less likely than those lacking only geometric information, then a lidar odometry algorithm that leverages both types of information will be more robust than an algorithm that relies only on one type, all other things being equal. Robustness is desirable because it makes performance predictable. The main contribution in this thesis is a lidar odometry algorithm that uses both appearance-based intensity landmarks as well as geometric landmarks to model the scene. The intensity landmarks are gradient edges that model features in the environment such as lane markings while the geometric…

Subjects/Keywords: lidar; odometry; maximum-likelihood estimation; continuous time; features; autonomous robotics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Skikos, B. A. P. (2019). LIDAR Odometry with Joint Geometric and Appearance Landmarks. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14518

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Skikos, Benjamin Anargyros Peregrine. “LIDAR Odometry with Joint Geometric and Appearance Landmarks.” 2019. Thesis, University of Waterloo. Accessed April 22, 2019. http://hdl.handle.net/10012/14518.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Skikos, Benjamin Anargyros Peregrine. “LIDAR Odometry with Joint Geometric and Appearance Landmarks.” 2019. Web. 22 Apr 2019.

Vancouver:

Skikos BAP. LIDAR Odometry with Joint Geometric and Appearance Landmarks. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2019 Apr 22]. Available from: http://hdl.handle.net/10012/14518.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Skikos BAP. LIDAR Odometry with Joint Geometric and Appearance Landmarks. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14518

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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