| Author: | Wang, Hao |
| Title: | Vision-based motion control for a four-wheel drive mobile robot |
| Degree: | M.Sc. |
| Year: | 2020 |
| Subject: | Mobile robots Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Mechanical Engineering |
| Pages: | xii, 113 pages : color illustrations |
| Language: | English |
| Abstract: | Autonomous Mobile Robots are ideal platforms for a wide range of applications both in indoor and outdoor environments. Most wheeled mobile robots have very simple passive suspension based on conventional mass-spring-damper methods, which bring a trade-off between loading capacity and vibration isolation. This study presents a new type 4-WD (Four-wheel Drive) mobile robot base with four passive suspensions, which is constructed by using a bio-inspired animal-limb-like structure, to guarantee both loading capacity and vibration isolation performance. With the new bio-inspired suspension, the loading capacity, riding comfort, and obstacle negotiation capability of the robot in various rough ground environments can be significantly enhanced. Besides, the motion control and state estimation of the 4-WD mobile robot has become another difficult problem restricting mobile robots in various application. A model predictive control (MPC) architecture is adopted for optimizations of mobile robot trajectory tracking. And a visual-inertial multi-sensor fusion method is used for robot state estimation, and an advanced vision-based autonomous localization and navigation named V-SLAM approach is also realized. Simulations and experimental results demonstrate that the novel passive suspension can efficiently absorb strong shock induced by obstacle crossing and hence guarantee smooth motion in various environments. The MPC controller and visual-inertial odometry (VIO) can effectively improve localization and trajectory tracking accuracy. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 5224.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 8.85 MB | Adobe PDF | View/Open |
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