A Controllable Agent by Subgoals in Path Planning Using Goal-Conditioned Reinforcement Learning
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DOI: 10.1109/access.2023.3264264
Abstract: The aim of path planning is to search for a path from the starting point to the goal. Numerous studies, however, have dealt with a single predefined goal. That is, an agent who has completed… read more here.
Keywords: reinforcement learning; agent; path planning; goal conditioned ... See more keywords
Learning Goal Conditioned Socially Compliant Navigation From Demonstration Using Risk-Based Features
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DOI: 10.1109/lra.2020.3048657
Abstract: One of the main challenges of operating mobile robots in social environments is the safe and fluid navigation therein, specifically the ability to share a space with other human inhabitants by complying with the explicit… read more here.
Keywords: socially compliant; goal conditioned; compliant navigation; feature ... See more keywords
Learning Multi-Object Dense Descriptor for Autonomous Goal-Conditioned Grasping
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DOI: 10.1109/lra.2021.3062300
Abstract: In a goal-conditioned grasping task, a robot is asked to grasp the objects designated by a user. Existing methods for goal-conditioned grasping either can only handle relatively simple scenes or require extra user annotations. This… read more here.
Keywords: dense descriptor; conditioned grasping; learning multi; goal conditioned ... See more keywords
Weakly Supervised Disentangled Representation for Goal-Conditioned Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3141148
Abstract: Goal-conditioned reinforcement learning is a crucial yet challenging algorithm which enables agents to achieve multiple user-specified goals when learning a set of skills in a dynamic environment. However, it typically requires millions of the environmental… read more here.
Keywords: representation; disentangled representation; conditioned reinforcement; reinforcement learning ... See more keywords
Hierarchical Planning Through Goal-Conditioned Offline Reinforcement Learning
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DOI: 10.48550/arxiv.2205.11790
Abstract: Offline Reinforcement learning (RL) has shown potent in many safe-critical tasks in robotics where exploration is risky and expensive. However, it still struggles to acquire skills in temporally extended tasks. In this paper, we study… read more here.
Keywords: reinforcement learning; offline reinforcement; level; hierarchical planning ... See more keywords