| Autor: |
Arya Rajiv Chaloli, Karthik K Bhat, Vishwas N S |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
2019 Third International Conference on Inventive Systems and Control (ICISC). |
| DOI: |
10.1109/icisc44355.2019.9036461 |
| Popis: |
Conventional approaches to solving the Gait-Generation problem in humanoids are usually static in nature and are modeled based on a particular environment. These approaches can work well in a constrained context but fail to adapt to different environments. Hence turning our view and drawing inspiration from the various processes in nature, observing its principles and understanding the underlying concepts behind them, greatly improves our perspective in tackling this problem. There has been significant research in particular areas of such an approach yet the integration of these principles to form a wholesome approach has not been looked at with great detail. The approach taken intends to solve this problem and generate gait on a humanoid robot (the INDRA platform) by implementing a biologically inspired control approach called Central Pattern Generator (CPG) with neural oscillators. The parameters of the neural oscillator are tuned using Genetic algorithms and a policy is created to help the robot adapt to new environments of which there is no previous knowledge with the help of Reinforcement Learning. Therefore, this paper attempts to bring out a solution that combines multiple biologically derived approaches to generate a robust and stable gait. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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