Continuous reinforcement learning to adapt multi-objective optimization online for robot motion
This article introduces a continuous reinforcement learning framework to enable online adaptation of multi-objective optimization functions for guiding a mobile robot to move in changing dynamic environments. The robot with this framework can continuously learn from multiple or changing environments...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2020-03-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.1177/1729881420911491 |