Applied & Human-Centered · Computer Science & AI
Robotics
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4,418 papers, from 4 September 2026 to 5 November 2026: 4,418 arXiv preprints.
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Newest papers, page 133
DeepJEPA: Scaling World Models from Within
World-model planners typically scale outward by rolling farther, sampling more trajectories, or optimizing longer, while assigning the same computation to every imagined transition.Whole-Body Aerial Grasping and Lifting via Partial Visual Observations
Aerial grasp-and-lift tasks require whole-body coordination across approach, acquisition, and lifting under partial target observations.Towards a General Humanoid Loco-Manipulation Model via Egocentric Whole-Body Human Data Pretraining
Humanoid whole-body manipulation has advanced rapidly, enabling policies to coordinate locomotion, posture, bimanual interaction, and dexterous hand movements.ScaffoldM3C: A Multimodal Sequential Monte Carlo Framework for Generative Stable Construction Planning
Autonomously constructing physically realizable 3D structures remains a significant challenge due to combinatorial action spaces, interchangeable components, equifinal assembly sequences, and strict…Same Scene, Different Task: Skill Alignment for Compositional Generalization in VLAs
Vision-language-action (VLA) models often struggle to generalize to skill combinations absent from their fine-tuning demonstrations, even when every constituent skill has been demonstrated.Admissibility-Preserving Control for Multi-Input Systems with Joint Capacity Constraints
This paper addresses the control of multi-input strict-feedback nonlinear systems subject to a joint capacity constraint, in which the admissible input set is a coupled subset of the individual…Does Continual Imitation Learning Remain Grounded? A Language-Perturbed Benchmark for Robotic Task Retention
Continual imitation learning evaluates whether a robot can learn new knowledge without forgetting previously learned skills.Token-World: World Modeling in Vision-Language Model Token Space for Robot Manipulation
A common approach to world-model simulation for vision-language-action (VLA) systems is to predict future RGB observations and then re-encode them into policy inputs, introducing an indirect…When Reasoning Helps Action: Monitoring and Steering Chain-of-Thought in Vision-Language-Action Policies
Reasoning-enabled VLA policies expose chain-of-thought (CoT) traces that appear to explain and guide their actions, creating a potential interface for runtime safety through reasoning monitoring and…MIKASA-Robo-VLA: Benchmarking Memory in VLA Models for Long-Horizon Manipulation
Vision-language-action policies often see only one or a few recent frames, which makes it difficult to evaluate how they use information that disappears during a task.Spatial Strategies, Not Actions: Vector-Quantized Geodesics as Tools for LLM-Driven Agents
Large language model (LLM) based agents are often criticized for lacking spatial understanding and mainly exploiting statistical text patterns.TacDyn-WAM: Learning Implicit Tactile Dynamics in a Heterogeneous Visuo-Tactile World Action Model
World action models improve robotic manipulation by conditioning actions on predicted futures, yet existing tactile variants largely inherit video-generation pipelines that reconstruct future…Learning Transferable Skills using Goal-Conditioned Bisimulation
Unsupervised skill discovery has emerged as a promising approach for leveraging reward-free datasets to pretrain general-purpose policies.Toward Humanoid Robots in Construction: A Teleoperation Feasibility Study
We present a teleoperation system that enables a single operator to perform construction tasks on a Unitree G1 humanoid, combining extended reality (XR) based upper body control with pedal-based…CF-JEPA: Improving Robustness of JEPA World Models via Controllability Factorization
Controlling an agent with vision requires being able to separate useful information from irrelevant background information.Reward as Observation: Learning Reward-Based Policies for Rapid Adaptation
This paper explores a reward-based policy to achieve zero-shot transfer between source and target environments with completely different observation spaces.Measuring Asset and Scene Reconstruction Effects in Real-to-Sim Robot Evaluation
Simulated evaluation is increasingly used alongside real-world evaluation of robot policies because it is cheaper and easier to repeat; however, its value depends on how closely its outcomes track…DITTO-X: Forward and Reverse Teleoperation for Dexterous Manipulation and Human Intervention
Teleoperated demonstrations are a primary source of data for robot manipulation, and teleoperated interventions are a primary mechanism for correcting policies at deployment.ECoMEM: Explicit Concept Memory for Memory-Dependent Robot Control
A robot may lose sight of an object it must later retrieve, need to recall what a person demonstrated earlier, or track which steps of a task it has already completed.Getting Out and Getting Back: World and Behavior Grounding in Real2Sim2Real Co-Training
Simulation can expand scarce real demonstrations for co-training, yet how world fidelity and similarity to human behavior affect policy performance remains unclear.