Safe Reinforcement Learning for Arm Manipulation with Constrained Markov Decision Process

In the world of human–robot coexistence, ensuring safe interactions is crucial. Traditional logic-based methods often lack the intuition required for robots, particularly in complex environments where these methods fail to account for all possible scenarios. Reinforcement learning has shown promise...

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Bibliographic Details

Published in:	Robotics
Main Authors:	Patrick Adjei, Norman Tasfi, Santiago Gomez-Rosero, Miriam A. M. Capretz
Format:	Article
Language:	English
Published:	MDPI AG 2024-04-01
Subjects:	safe reinforcement learning constrained Markov decision process Lagrangian multiplier scalarized expected return UR5 arm robot
Online Access:	https://www.mdpi.com/2218-6581/13/4/63