Reinforcement Learning of Depth Stabilization with a Micro Diving Agent @ICRA-cg8kk
Reinforcement Learning of Depth Stabilization with a Micro Diving Agent @ICRA-cg8kk
Uploaded May 2018 | Updated September 2026, 3 weeks ago
ICRA 2018 Spotlight Video
Interactive Session Thu AM Pod P.4
Authors: Brinkmann, Gerrit; Duecker, Daniel Andre; Kreuzer, Edwin; Solowjow, Eugen; Bessa, Wallace M.
Title: Reinforcement Learning of Depth Stabilization with a Micro Diving Agent

Abstract:
Reinforcement learning (RL) allows robots to solve control tasks through interaction with their environment. In this paper we study a value-function- and model-based RL framework, which is suitable for computationaly limited robots. We develop a diving agent, which uses the RL algorithm for underwater depth stabilization. Simulations and experiments with the micro diving agent demonstrate its ability to learn the depth stabilization task.
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ICRA 2018 |

Reinforcement Learning of Depth Stabilization with a Micro Diving Agent

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