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Unsupervised Perceptual Rewards for Imitation Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Robot Programming by Demonstration
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A survey of robot learning from demonstration
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Bayesian Inverse Reinforcement Learning
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ImageNet: A large-scale hierarchical image database
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Rethinking the Inception Architecture for Computer Vision
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Imitation Learning of Dual-Arm Manipulation Tasks in Humanoid Robots
inferredcites →https://doi.org/10.1109/icra.2013.6630592openalex-snapshot
Scalable reward learning from demonstration
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Learning to predict phases of manipulation tasks as hidden states
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Deep spatial autoencoders for visuomotor learning
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Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours
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SE3-nets: Learning rigid body motion using deep neural networks
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Path integral guided policy search
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Autonomous reinforcement learning on raw visual input data in a real world application
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Nonparametric Bayesian reward segmentation for skill discovery using inverse reinforcement learning
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A Formal Study of Shot Boundary Detection
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IMITATION LEARNING OF DUAL-ARM MANIPULATION TASKS IN HUMANOID ROBOTS
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Apprenticeship learning via inverse reinforcement learning
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Incremental learning of gestures by imitation in a humanoid robot
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Learning grounded finite-state representations from unstructured demonstrations
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SWIRL: A sequential windowed inverse reinforcement learning algorithm for robot tasks with delayed rewards
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Maximum Entropy Inverse Reinforcement Learning
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Unsupervised Perceptual Rewards for Imitation Learning
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Relative Entropy Policy Search
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Perceptual Reward Functions
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Path Integral Guided Policy Search
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A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models
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Unsupervised Perceptual Rewards for Imitation Learning
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A Generalized Path Integral Control Approach to Reinforcement Learning
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A User Study on Kinesthetic Teaching of Redundant Robots in Task and Configuration Space
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Chain-of-Modality: Learning Manipulation Programs from Multimodal Human Videos with Vision-Language-Models
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Self-supervised 6-DoF Robot Grasping by Demonstration via Augmented Reality Teleoperation System
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Comparison and Implementation of High Cited Inverse Reinforcement Learning Algorithms in Object World
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Visual Task Progress Estimation with Appearance Invariant Embeddings for Robot Control and Planning
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Playful Interactions for Representation Learning
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Behaviour Learning with Adaptive Motif Discovery and Interacting Multiple Model
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Learning Object Manipulation Skills from Video via Approximate Differentiable Physics
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Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos
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Ag2Manip: Learning Novel Manipulation Skills with Agent-Agnostic Visual and Action Representations
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KT-Imitation: Efficient Visual Imitation for Autonomous Navigation Based on Keypoint Timeline
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GOSELO: Goal-Directed Obstacle and Self-Location Map for Robot Navigation Using Reactive Neural Networks
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Self-Supervised Correspondence in Visuomotor Policy Learning
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Universal Planning Networks
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Perceptual Values from Observation
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Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning
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Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning
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Transformers for One-Shot Visual Imitation
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Reinforcement Learning with Videos: Combining Offline Observations with Interaction
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Learning Object Manipulation Skills via Approximate State Estimation from Real Videos
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Semi-supervised reward learning for offline reinforcement learning
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XIRL: Cross-embodiment Inverse Reinforcement Learning
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A Simple Approach to Continual Learning by Transferring Skill Parameters
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Visual Goal-Directed Meta-Learning with Contextual Planning Networks
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Learning Behaviors from a Single Video Demonstration Using Human Feedback
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Détection et estimation de pose d'instances d'objet rigide pour la manipulation robotisée
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Learning sensori-motor mappings using little knowledge : application to manipulation robotics
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Visual Object Manipulation Based on Exploration Guided by Demonstration
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