首页|New Findings from Federal University Minas Gerais in the Area of Robotics Described (Generalization In Deep Reinforcement Learning for Robotic Navigation By Reward Shaping)
New Findings from Federal University Minas Gerais in the Area of Robotics Described (Generalization In Deep Reinforcement Learning for Robotic Navigation By Reward Shaping)
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IEEE
A new study on Robotics is now available. According to news reporting out of Belo Horizonte, Brazil, by NewsRx editors, research stated, “This paper addresses the application of Deep Reinforcement Learning (DRL) methods in the context of local navigation, i.e., a robot moves towards a goal location in unknown and cluttered workspaces equipped only with limited-range exteroceptive sensors. Collision avoidance policies based on DRL present advantages, but they are quite susceptible to local minima, once their capacity to learn suitable actions is limited to the sensor range.”
Belo HorizonteBrazilSouth AmericaEmerging TechnologiesMachine LearningReinforcement LearningRoboticsRobotsFederal University Minas Gerais
NETL
NSTL
IEEE
