RLBench
Canonical44papers using it
2025first seen
RLBench is a benchmark dataset that contains a variety of continuous manipulation tasks designed to evaluate robotic control and learning algorithms in simulated environments.
Papers using RLBench (44)
- Demo-JEPA: Joint-Embedding Predictive Architecture for One-shot Cross-Embodiment ImitationLearning Structural Latent Points for Efficient Visual Representations in Robotic ManipulationPointACT: Vision-Language-Action Models with Multi-Scale Point-Action InteractionTGM-VLA: Task-guided Mixup For Sampling-efficient And Robust Robotic ManipulationSpeculative Policy Orchestration: A Latency-resilient Framework For Cloud-robotic ManipulationST-VLA: Enabling 4D-Aware Spatiotemporal Understanding for General Robot ManipulationLearning To See And Act: Task-aware Virtual View Exploration For Robotic ManipulationMulti-modal Manipulation Via Multi-modal Policy ConsensusSam2act: Integrating Visual Foundation Model With A Memory Architecture For Robotic Manipulation3D Flowmatch Actor: Unified 3D Policy For Single- And Dual-arm ManipulationMemory Transfer Planning: Llm-driven Context-aware Code Adaptation For Robot ManipulationScaling Cross-environment Failure Reasoning Data For Vision-language Robotic ManipulationGPA-RAM: Grasp-pretraining Augmented Robotic Attention Mamba For Spatial Task LearningThe Unreasonable Effectiveness Of Discrete-time Gaussian Process Mixtures For Robot Policy LearningImanip: Skill-incremental Learning For Robotic ManipulationNeSyC: A Neuro-symbolic Continual Learner For Complex Embodied Tasks In
Open DomainsGraspCorrect: Robotic Grasp Correction via Vision-Language Model-Guided
FeedbackGPA-RAM: Grasp-Pretraining Augmented Robotic Attention Mamba for Spatial Task LearningLearning Video Generation for Robotic Manipulation with Collaborative Trajectory ControlBridgeVLA: Input-Output Alignment for Efficient 3D Manipulation Learning with Vision-Language ModelsChain-of-Action: Trajectory Autoregressive Modeling for Robotic ManipulationFlowRAM: Grounding Flow Matching Policy with Region-Aware Mamba Framework for Robotic ManipulationMinD: Learning A Dual-System World Model for Real-Time Planning and Implicit Risk AnalysisRoboPearls: Editable Video Simulation for Robot ManipulationActor-Critic for Continuous Action Chunks: A Reinforcement Learning Framework for Long-Horizon Robotic Manipulation with Sparse RewardLarge Pre-Trained Models for Bimanual Manipulation in 3DMemory Transfer Planning: LLM-driven Context-Aware Code Adaptation for Robot ManipulationSpatialActor: Exploring Disentangled Spatial Representations for Robust Robotic ManipulationScaling Cross-Environment Failure Reasoning Data for Vision-Language Robotic ManipulationVERM: Leveraging Foundation Models to Create a Virtual Eye for Efficient 3D Robotic ManipulationLearning Geometrically-Grounded 3D Visual Representations for View-Generalizable Robotic ManipulationGSR: Learning Structured Reasoning for Embodied ManipulationTGM-VLA: Task-Guided Mixup for Sampling-Efficient and Robust Robotic ManipulationHyperbolic Multiview Pretraining for Robotic ManipulationCortical Policy: A Dual-Stream View Transformer for Robotic ManipulationThe Unreasonable Effectiveness of Discrete-Time Gaussian Process
Mixtures for Robot Policy LearningFMimic: Foundation Models are Fine-grained Action Learners from Human VideosLearning to See and Act: Task-Aware Virtual View Exploration for Robotic ManipulationADPro: a Test-time Adaptive Diffusion Policy via Manifold-constrained Denoising and Task-aware Initialization for Robotic ManipulationEgo-centric Predictive Model Conditioned on Hand TrajectoriesMulti-Modal Manipulation via Multi-Modal Policy ConsensusViReSkill: Vision-Grounded Replanning with Skill Memory for LLM-Based Planning in Lifelong Robot LearningTowards Reliable Code-as-Policies: A Neuro-Symbolic Framework for Embodied Task PlanningDynaRend: Learning 3D Dynamics via Masked Future Rendering for Robotic Manipulation