Abstract
Explainability is becoming an important topic in artificial intelligence (AI). A well explainable system can increase the trust in the application of that system. The same holds for robotics where the walking gait controller can be some AI system. We will show that a simple and explainable controller that enables an energy efficient walking gait and can handle uneven terrains, can be developed by a well structured design method. The main part of the controller consist of three simple neural networks with 4, 6 and 8 neurons. So, although creating a stable and energy efficient walking gait is a complex problem, it can be generated without some deep neural network or some complex mathematical model.
| Original language | English |
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| Title of host publication | Proceedings of the Reference AI & ML Conference for Belgium, Netherlands & Luxemburg |
| Subtitle of host publication | 31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning, BNAIC/BENELEARN 2019 |
| Volume | 2491 |
| Publication status | Published - 1 Jan 2019 |
| Event | 31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning - Brussels, Belgium Duration: 6 Nov 2019 → 8 Nov 2019 Conference number: 31 |
Publication series
| Series | CEUR Workshop Proceedings |
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| ISSN | 1613-0073 |
Conference
| Conference | 31st Benelux Conference on Artificial Intelligence and the 28th Belgian Dutch Conference on Machine Learning |
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| Abbreviated title | BNAIC/BENELEARN 2019 |
| Country/Territory | Belgium |
| City | Brussels |
| Period | 6/11/19 → 8/11/19 |