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Autonomous Robots in Dynamic Indoor Environments: Localization and Person-Following

Autonomous Robots in Dynamic Indoor Environments: Localization and Person-Following

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Title: Autonomous Robots in Dynamic Indoor Environments: Localization and Person-Following
Author: Sahdev, Raghavender
Abstract: Autonomous social robots have many tasks that they need to address such as localization, mapping, navigation, person following, place recognition, etc. In this thesis we focus on two key components required for the navigation of autonomous robots namely, person following behaviour and localization in dynamic human environments. We propose three novel approaches to address these components; two approaches for person following and one for indoor localization. A convolutional neural networks based approach and an Ada-boost based approach are developed for person following. We demonstrate the results by showing the tracking accuracy over time for this behaviour. For the localization task, we propose a novel approach which can act as a wrapper for traditional visual odometry based approaches to improve the localization accuracy in dynamic human environments. We evaluate this approach by showing how the performance varies with increasing number of dynamic agents present in the scene. This thesis provides qualitative and quantitative evaluations for each of the approaches proposed and show that we perform better than the current approaches.
Subject: Artificial intelligence
Keywords: Robotics
Computer vision
Person following
Person following robot
Tracking
Person tracking
Target tracking
Localization
Visual odometry
Wheel odometry
Humans
Dynamic environments
Autonomous robots
CNN tracker
Stereo vision
Ada-boosting
Real-time tracking
Social robots
Type: Electronic Thesis or Dissertation
Rights: Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
URI: http://hdl.handle.net/10315/34572
Supervisor: Tsotsos, John K.
Degree: MSc - Master of Science
Program: Computer Science
Exam date: 2018-03-22
Publish on: 2018-05-28

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