Deep Reinforcement Learning With Optimized Reward Functions for Robotic Trajectory Planning
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2932257
Abstract: To improve the efficiency of deep reinforcement learning (DRL)-based methods for robotic trajectory planning in the unstructured working environment with obstacles. Different from the traditional sparse reward function, this paper presents two brand-new dense reward… read more here.
Keywords: reward functions; reinforcement learning; trajectory; deep reinforcement ... See more keywords
Solving Robotic Trajectory Sequential Writing Problem via Learning Character's Structural and Sequential Information.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3194700
Abstract: The writing sequence of numerals or letters often affects aesthetic aspects of the writing outcomes. As such, it remains a challenge for robotic calligraphy systems to perform, mimicking human writers' implicit intention. This article presents… read more here.
Keywords: information; system; solving robotic; writing ... See more keywords