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ETD Abstract Container

Abstract Header

A Deep-Learning Approach to Evaluating the Navigability of Off-Road Terrain from 3-D Imaging

Pech, Thomas Joel
http://rave.ohiolink.edu/etdc/view?acc_num=case1496377449249936

Abstract Details

2017, Master of Sciences (Engineering), Case Western Reserve University, EECS - Computer and Information Sciences.
This work investigates a strategy for evaluating the navigability of terrain from 3-D imaging. Labeled training data was automatically generated by running a simulation of a mobile robot nai¨vely exploring a virtual world. During this exploration, sections of terrain were perceived through simulated depth imaging and saved with labels of safe or unsafe, depending on the outcome of the robot's experience driving through the perceived regions. This labeled data was used to train a deep convolutional neural network. Once trained, the network was able to evaluate the safety of perceived regions. The trained network was shown to be effective in achieving safe, autonomous driving through novel, challenging, unmapped terrain.
Wyatt Newman (Advisor)
Cenk Cavusoglu (Committee Member)
Michael Lewicki (Committee Member)
84 p.
Computer Science; Robotics; Robots
Mobile robots, Autonomous Navigation, Machine Learning, Artificial Neural Networks, Terrain, Simulation, Training Data, Data Generation, Labeling, Classifiers, Convolutional Neural Networks, Point Clouds, Perception, Prediction, Artificial Intelligence

Recommended Citations

Citations

  • Pech, T. J. (2017). A Deep-Learning Approach to Evaluating the Navigability of Off-Road Terrain from 3-D Imaging [Master's thesis, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1496377449249936

    APA Style (7th edition)

  • Pech, Thomas. A Deep-Learning Approach to Evaluating the Navigability of Off-Road Terrain from 3-D Imaging. 2017. Case Western Reserve University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1496377449249936.

    MLA Style (8th edition)

  • Pech, Thomas. "A Deep-Learning Approach to Evaluating the Navigability of Off-Road Terrain from 3-D Imaging." Master's thesis, Case Western Reserve University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1496377449249936

    Chicago Manual of Style (17th edition)

case1496377449249936
317
© 2017, some rights reserved.Creative Commons License A Deep-Learning Approach to Evaluating the Navigability of Off-Road Terrain from 3-D Imaging by Thomas Joel Pech is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.