碩士 / 國立臺灣大學 / 機械工程學研究所 / 106 / Adjusting dynamic motions according to the environment has been an important research topic in recent years. The main contribution of this thesis is the development of autonomous gait and direction switching on a leg-wheel transformable quadruped robot, TurboQuad-V, by using real-time color and depth information of the terrain combined with the original bio-inspired CPG structure.
Color image is used to classify different types of landscape by using Convolution Neural Network model, which is trained with the database collected in this research. Depth image is transferred to elevation grids to represent the geometry distribution of the terrain, and the optimized path as well as the height distributions along the route can be calculated.
This research also focuses on the development of the dynamic simulation using single-leg-wheel model. The simulation runs different gaits on various simplified terrains while considering slip effect and contact geometry. With the analysis of indexes such as power efficiency, the ability to overcome obstacles and the height variation during motions, suitable operating points of each gait according to different kinds of terrain can be concluded.
With the integration of information from the image processing and the switching policy of each gait, TurboQuad-V is proved to have the ability to perform autonomous gait switching and basic obstacle avoidance by the experiments conducted on multiple environment.
| Identifer | oai:union.ndltd.org:TW/106NTU05489067 |
| Date | January 2018 |
| Creators | Ting-Hao Wang, 王霆皓 |
| Contributors | Pei-Chun Lin, 林沛群 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 149 |
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