<p> Walking robots consume considerable amounts of power, which leads to short mission times. Many of the tasks that require the use of walking robots, rather than wheeled, often require extended periods of time between the possibility of charging. Therefore, it is extremely important that, whenever possible, the gait a walking robot uses is as efficient as possible in order to extend overall mission time. Many approaches have been used in order to optimize the gait of a hexapod robot; however, little research has been done on how enabling the leg segments of a hexapod to extend will impact the efficiency of its gait. In this thesis, a joint space model is defined that includes both rotational joints as well as prismatic joints for expanding and contracting individual leg segments. A genetic algorithm (GA) is used to optimize the efficiency of a gait using the joint space based on a tripod gait. Other considerations for the gait include stability and dragging, which affects overall efficiency of a gait. The results of preliminary runs of the GA show the impacts of changing the weights of a multi-objective function, the number of generations, the number of parents retained between generations and the mutation rate. Further experiments show the impact of dynamic leg lengths on the overall efficiency of a hexapod tripod gait.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10684042 |
| Date | 23 January 2018 |
| Creators | Cafarelli, Ryan |
| Publisher | Southern Illinois University at Edwardsville |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
Page generated in 0.009 seconds