PhD Defense by Pileun Kim

Event Details
  • Date/Time:
    • Thursday November 12, 2020 - Friday November 13, 2020
      4:00 pm - 5:59 pm
  • Location: Remote: Blue Jeans
  • Phone:
  • URL: Bluejeans
  • Email:
  • Fee(s):
    N/A
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Summaries

Summary Sentence: Effective navigation and mapping of a cluttered environment using a mobile robot

Full Summary: No summary paragraph submitted.

Ph.D. Thesis Defense Announcement

Effective navigation and mapping of a cluttered environment using a mobile robot

 

by

Pileun Kim

 

Advisor(s):

Dr. Yong K. Cho

 

Committee Members:

Dr. Eric Marks (CEE), Dr. Jun Ueda (ME), Dr. W. Hong Yeo (ME), Dr. Chao Wang (Louisiana State University)

 

Date & Time: Nov. 12th, 4-6 pm

Location: https://bluejeans.com/801890097

 

Today, the as-is three-dimensional point cloud acquisition process for understanding scenes of interest, monitoring construction progress, and detecting safety hazards uses a laser scanning system mounted on mobile robots, which enables it faster and more automated, but there is still room for improvement. The main disadvantage of data collection using laser scanners is that point cloud data is only collected in a scanner's line of sight, so regions in three-dimensional space that are occluded by objects are not observable. To solve this problem and obtain a complete reconstruction of sites without information loss, scans must be taken from multiple viewpoints. This thesis describes how such a solution can be integrated into a fully autonomous mobile robot capable of generating a high-resolution three-dimensional point cloud of a cluttered and unknown environment without a prior map.  First, the mobile platform estimates unevenness of terrain and surrounding environment. Second, it finds the occluded region in the currently built map and determines the effective next scan location. Then, it moves to that location by using grid-based path planner and unevenness estimation results. Finally, it performs the high-resolution scanning that area to fill out the point cloud map. This process repeats until the designated scan region filled up with scanned point cloud. The mobile platform also keeps scanning for navigation and obstacle avoidance purposes, calculates its relative location, and builds the surrounding map while moving and scanning, a process known as simultaneous localization and mapping. The proposed approaches and the system were tested and validated in an outdoor construction site and a simulated disaster environment with promising results.

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Graduate Studies

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Faculty/Staff, Public, Undergraduate students
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Phd Defense
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Oct 26, 2020 - 1:59pm
  • Last Updated: Oct 26, 2020 - 1:59pm