Papers Continuous Control
“Continuous Control” 태그가 달린 논문 1,432편 · 필터 해제
Unsupervised Behavioral Compression: Learning Low-Dimensional Policy Manifolds through State-Occupancy Matching
Deep Reinforcement Learning (DRL) is widely recognized as sample-inefficient, a limitation attributable in part to the high dimensionality and substantial functional redundancy inherent to the policy parameter space. A r…
Reinforcement LearningContinuous ControlEmergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories
Scaling robot learning to long-horizon tasks remains a formidable challenge. While end-to-end policies often lack the structural priors needed for effective long-term reasoning, traditional neuro-symbolic methods rely he…
Continuous ControlDecentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning
Decentralized cooperative pursuit in cluttered environments is challenging for autonomous aerial swarms, especially under partial and noisy perception. Existing methods often rely on abstracted geometric features or priv…
Multi-agent Reinforcement LearningContinuous ControlLanguage-Conditioned World Modeling for Visual Navigation
We study language-conditioned visual navigation (LCVN), in which an embodied agent is asked to follow a natural language instruction based only on an initial egocentric observation. Without access to goal images, the age…
Trajectory PredictionContinuous ControlVisual NavigationEvolutionary Warm-Starts for Reinforcement Learning in Industrial Continuous Control
Reinforcement learning (RL) is still rarely applied in industrial control, partly due to the difficulty of training reliable agents for real-world conditions. This work investigates how evolution strategies can support R…
Reinforcement LearningContinuous ControlCharacterizing the onset and offset of motor imagery during passive arm movements induced by an upper-body exoskeleton
Two distinct technologies have gained attention lately due to their prospects for motor rehabilitation: robotics and brain-machine interfaces (BMIs). Harnessing their combined efforts is a largely uncharted and promising…
Continuous ControlMixed-Integer vs. Continuous Model Predictive Control for Binary Thrusters: A Comparative Study
Binary on/off thrusters are commonly used for spacecraft attitude and position control during proximity operations. However, their discrete nature poses challenges for conventional continuous control methods. The control…
Continuous ControlSpectral Alignment in Forward-Backward Representations via Temporal Abstraction
Forward-backward (FB) representations provide a powerful framework for learning the successor representation (SR) in continuous spaces by enforcing a low-rank factorization. However, a fundamental spectral mismatch often…
Representation LearningContinuous ControlUnderstanding Behavior Cloning with Action Quantization
Behavior cloning is a fundamental paradigm in machine learning, enabling policy learning from expert demonstrations across robotics, autonomous driving, and generative models. Autoregressive models like transformer have …
Continuous ControlAutonomous DrivingEfficient Soft Actor-Critic with LLM-Based Action-Level Guidance for Continuous Control
We present GuidedSAC, a novel reinforcement learning (RL) algorithm that facilitates efficient exploration in vast state-action spaces. GuidedSAC leverages large language models (LLMs) as intelligent supervisors that pro…
Reinforcement LearningContinuous ControlThe Unreasonable Effectiveness of Text Embedding Interpolation for Continuous Image Steering
We present a training-free framework for continuous and controllable image editing at test time for text-conditioned generative models. In contrast to prior approaches that rely on additional training or manual user inte…
Continuous ControlVideo GenerationImage EditingShifting Uncertainty to Critical Moments: Towards Reliable Uncertainty Quantification for VLA Model
Vision-Language-Action (VLA) models enable general-purpose robotic policies by mapping visual observations and language instructions to low-level actions, but they often lack reliable introspection. A common practice is …
Continuous ControlTowards the Vision-Sound-Language-Action Paradigm: The HEAR Framework for Sound-Centric Manipulation
While recent Vision-Language-Action (VLA) models have begun to incorporate audio, they typically treat sound as static pre-execution prompts or focus exclusively on human speech. This leaves a significant gap in real-tim…
Continuous ControlStochastic Resetting Accelerates Policy Convergence in Reinforcement Learning
Stochastic resetting, where a dynamical process is intermittently returned to a fixed reference state, has emerged as a powerful mechanism for optimizing first-passage properties. Existing theory largely treats static, n…
Reinforcement LearningContinuous ControlZero-Shot Generalization from Motion Demonstrations to New Tasks
Learning motion policies from expert demonstrations is an essential paradigm in modern robotics. While end-to-end models aim for broad generalization, they require large datasets and computationally heavy inference. Conv…
Zero-shot GeneralizationContinuous ControlLearning Latent Proxies for Controllable Single-Image Relighting
Single-image relighting is highly under-constrained: small illumination changes can produce large, nonlinear variations in shading, shadows, and specularities, while geometry and materials remain unobserved. Existing dif…
Continuous ControlImage RelightingGoldenStart: Q-Guided Priors and Entropy Control for Distilling Flow Policies
Flow-matching policies hold great promise for reinforcement learning (RL) by capturing complex, multi-modal action distributions. However, their practical application is often hindered by prohibitive inference latency an…
Reinforcement LearningContinuous ControlAerialVLA: A Vision-Language-Action Model for UAV Navigation via Minimalist End-to-End Control
Vision-Language Navigation (VLN) for Unmanned Aerial Vehicles (UAVs) demands complex visual interpretation and continuous control in dynamic 3D environments. Existing hierarchical approaches rely on dense oracle guidance…
Vision-Language NavigationContinuous ControlDelightful Policy Gradient
Standard policy gradients weight each sampled action by advantage alone, regardless of how likely that action was under the current policy. This creates two pathologies: within a single decision context (e.g. one image o…
Continuous ControlST-VLA: Enabling 4D-Aware Spatiotemporal Understanding for General Robot Manipulation
Robotic manipulation in open-world environments requires reasoning across semantics, geometry, and long-horizon action dynamics. Existing hierarchical Vision-Language-Action (VLA) frameworks typically use 2D representati…
Continuous ControlRobot Manipulation