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- Robot Navigation and Canine Welfare: A Pilot Study Surfacing Challenges for Cross-Species Legibility and Proxy Validity
A pilot study in a real home environment evaluated a "curve-out" navigation maneuver for canine welfare: a lateral arcing pass-by trajectory triggered at the dog's alert distance. Contrary to the hypothesis, the maneuver elicited a stronger stress response than a straight-line baseline. The authors argue that the maneuver's discontinuous execution, with the robot stopping and reorienting multiple times to approximate the arc, undermined behavioral legibility, which itself became a stressor. The study thus raises the legibility of robot behavior to non-humans and proxy stimulus validity as structural challenges for animal-machine interaction (AMI).
arXiv cs.RO ·
- AquaProbe: A Method for Adapting Underwater Vision Models by Allocating LoRA Rank According to Water Type
AquaProbe proposes an underwater image adaptation method for frozen vision models: it measures how domain differences are distributed across encoder depths using paired clean images and physically rendered images, then allocates a fixed LoRA rank budget according to that distribution.
arXiv cs.RO ·
- How a team that cannot communicate learns its own state from an opponent's reactions
A game theory and multi-agent study proposes that a team unable to communicate can learn information no single member can see by reading the opponent's reaction to the group as a whole (a tell); one tell can substitute for messaging among all members. In a solved Gaussian model, the team obtains the truth by committing not to use all of the information, and retains the hidden cost the opponent would have paid; an exact test can determine when this conclusion holds in finite games. The study also analyzes how trust is allocated, noting that two interchangeable members responding in different ways can substitute for a single member's private random source.
arXiv cs.RO ·
- ID-WM: A Hierarchical World Model Decoupling State Reachability from Local Control
The authors propose ID-WM (Implicit Dynamics World Models), a hierarchical world model in which a high-level model samples feasible transitions on the state manifold and a low-level world model acts as an inverse dynamics solver to ground those transitions into precise actions. On three navigation and manipulation test suites, it improves over existing policies and diffusion planners by 38.5%, and by 135% over single-layer world model MPC in complex unseen long-horizon configurations.
arXiv cs.RO ·
- RoboArchitect: Automating the Design of Robotic Agents with Persistent Memory
RoboArchitect lets a coding model observe robot rollouts, diagnose failures, and iteratively revise the agent harness around a frozen policy. Without updating any model weights, it raises average success from 9.7% to 43.3% (4.5x) on unseen scenes and from 12.7% to 40.2% (3.2x) on unseen tasks.
arXiv cs.RO ·
- ROOF: A Learning Method for Humanoid Fall Recovery in Overhead-Constrained Environments
ROOF proposes a reinforcement learning method with contact-supported geometric escape guidance that enables proprioception-only humanoid robots to first create clearance and then complete the rise under overhead obstacles. In simulation, the recovery success rate was 88.5% under plates that can only be lifted, compared with 18.9% without geometric guidance; it was 98.6% under free plates with randomized size, mass, and placement. After deployment on a Unitree G1, the policy successfully recovered in 95 of 150 attempts across seven real-world obstacle scenes, including furniture and multi-object arrangements not seen in training.
arXiv cs.RO ·
- REA: A Routed Embodied Agent Runtime for Asynchronous Brain-Cerebellum Control
The authors propose REA, a routed embodied agent runtime that lets a reasoning-focused System 2, an embodied router System 1, and reactive System 0 policies cooperate within a single runtime, with the core rule that a running policy never waits on the brain.
arXiv cs.RO ·
- Hybrid Path Planning Framework for Assistive Wheelchair Navigation in Dynamic Pedestrian Environments
A study proposes a hybrid path planning framework for multi-goal navigation of assistive wheelchairs, using the Traveling Salesman Problem (TSP) for global task ordering combined with the Potential Field (PF) method and heuristic local planners such as RRT and A* to achieve collision-free navigation, and develops two algorithms, TSP-PF-RRT and TSP-PF-A*. In Monte Carlo simulations of crowded and super-crowded scenarios, the framework achieves efficient multi-goal navigation in dynamic human environments containing heterogeneous static and dynamic obstacles, with TSP-PF-RRT producing fewer or zero collisions and shorter travel distances.
arXiv cs.RO ·
- Proof-Carrying Evolution: Language Models Design Formally Verifiable Controllers
The study proposes Proof-Carrying Evolution (PCE), in which a language model provides both a controller and its certificate during search; only candidates that pass certificate verification can be returned, and the deployed artifact is the control law together with its certificate. The authors compare four language models with classical search and synthesis methods on speed-limited docking, maneuvering-target pursuit, and SO(3) attitude control. Certificates for linear problems are verified using exact rational arithmetic; on SO(3), floating-point verification is followed by exact re-verification of each reported champion. The best run of each method also receives a Lean 4 proof.
arXiv cs.RO ·
- Nexus-VLA: Connecting Human and Robot Experience with a Shared Hierarchical Semantic Latent Space
The authors propose Nexus-VLA, a hybrid policy learning framework that enables cross-embodiment knowledge transfer through end-to-end human-robot joint training, allowing human manipulation experience to directly contribute to robot policy learning. The framework first establishes hierarchical cross-embodiment semantic alignment from task intent to fine-grained interactions, then encodes multi-level shared knowledge into a shared manipulation latent representation used directly for continuous action generation. In RoboCasa-GR1, OOD settings, and real-robot experiments, Nexus-VLA achieved an 80.5% task success rate on RoboCasa-GR1.
arXiv cs.RO ·
- Suspended fabric robotic manipulation surfaces: modeling, design space, and multimodule extension
This paper proposes a separable catenary model for suspended-fabric Robotic Manipulation Surfaces (RMS) that can quickly compute the surface shape for given actuator heights, as well as the actuator heights needed to achieve a desired local slope. The closed-form inverse solution lets a simple PID controller position objects on the fabric surface, and the model relates fabric length, module span, and actuator stroke to the reachable workspace, yielding a lower bound on minimum fabric length and design charts.
arXiv cs.RO ·
- Open-Source Knee Exoskeleton: Generating Biological Torque Control with Musculoskeletal Simulation
A research team has released an open-source knee exoskeleton built from off-the-shelf components, whose biological torque controller is generated entirely by simulation, requiring no training data collected on the target device. The method uses a muscle-driven imitation policy to reproduce squatting motions from a public biomechanics dataset, then distills the knee joint torque into an estimator that relies only on onboard sensors.
arXiv cs.RO ·
- Language-conditioned behavioral cloning for autonomous endoscope guidance
The study proposes language-conditioned behavioral cloning for autonomous endoscope guidance, defining 6 clinically relevant guidance behaviors and collecting 235 subtask demonstrations. In preliminary phantom experiments, a single visuomotor policy achieved 100% success on focus, overview, and stop, 80% on search-tip and follow-tip, and 50% on horizon leveling. The authors note that the failure modes indicate more complex guidance tasks require temporal context.
arXiv cs.RO ·
- Adaptive Coverage Algorithms for Mobile Ad Hoc Networks in Dynamic Worlds: CADENCE and DADENCE Extended to DPOCGAGP
The study extends two algorithms, CADENCE and its decentralized version DADENCE, to the dynamic version of POCGAGP (DPOCGAGP), adding two deployment-time perturbation settings, Agent Loss and World Change, for multi-agent systems to establish a fully covering communication network in unknown constrained spaces. On more than 4,500 benchmark test cases of varying scale and structure, the improved algorithms outperform another state-of-the-art benchmark algorithm. The work focuses on simulation benchmark evaluation and has not yet involved real-robot validation.
arXiv cs.RO ·
- Online Learning of Heterogeneous Locomotion Dynamics for Precise Mobile Manipulation
The study proposes an online method for learning closed-loop dynamics under a frozen locomotion policy, using a contaminated Gaussian model to distinguish predictable from unpredictable responses and combining a Gaussian process with random Fourier features to build an online learner that reduces bias from heterogeneous observations. Combined with model predictive control (MPC), the method predicts floating-base motion more accurately; in simulation and hardware experiments, end-effector tracking error was 0.01 m, and a finite-sample error bound for the online learning is provided.
arXiv cs.RO ·
- Movens-Zero: Scaling humanoid motion foundation models with large-scale human videos
The research team proposes Movens-Zero, a scalable understanding-generation-execution architecture that supports real-time closed-loop humanoid motion generation under text, speech, music, and video inputs. Its accompanying dataset, Movens-5M, is built from Internet videos through clip generation, quality filtering, semantic annotation, motion recovery, and physical refinement with humanoid retargeting. It contains 15 million human motion sequences and 5 million physically executable humanoid motion sequences, totaling over 10,000 hours.
This technical report presents a complete path for building a humanoid motion dataset from Internet videos and training a unified understanding-generation-execution model, offering a reference for data scale and architecture design.
arXiv cs.RO ·
- SimuGuard: Auditing Contact Artifacts in Simulation Benchmarks Such as LIBERO and RoboTwin
The authors propose SimuGuard, an auditing plugin for LIBERO, RoboTwin, RoboCasa, and RoboDojo that identifies failures caused by the simulator rather than the policy. On RoboTwin, the authors trace these failures to the physics engine's collision detection: when geometry is 1 to 2 centimeters apart, the engine reports a penetration of about 2 centimeters, and the solver ejects the object at several meters per second because the distance algorithm discards triangles below a fixed area threshold.
The original traces failures in simulation benchmarks to a physics engine collision detection constant and provides a before-and-after success rate comparison, which can serve as a reference for teams doing simulation evaluation.
arXiv cs.RO ·
- SketchMate: Building Sketch Models with VLMs for Zero-Shot Precision Insertion
SketchMate has a vision-language model build a sketch model for insertion tasks, consisting of a few geometric primitives and two mating coordinate frames, which a planner and compliant controller then execute. In a strict kinematic test of 69 simulated insertion episodes, the method inserted 88% of parts at the assembled pose, while ReKep and MOKA using the same VLM achieved no successful insertions.
arXiv cs.RO ·
- Integrating Low-Thrust Transfer Dynamics into POMDP Planning for On-Orbit Servicing Missions
This research models low-thrust (LT) orbital transfers within a partially observable Markov decision process (POMDP) for on-orbit servicing (OOS) mission planning, adding the servicing spacecraft's remaining propellant to the state space to support mass updates. High-thrust transfers are modeled with a precomputed transfer matrix, while low-thrust transfers are represented by an analytical GEO phase model, with propellant consumption and maneuver feasibility computed for given transfer-duration alternatives. In a simplified OOS scenario, SARSOP is used to solve and compare high-thrust and low-thrust policies, quantitatively assessing the feasibility and operational impact of the low-thrust option.
arXiv cs.RO ·
- Visual-Inertial-Encoder RGB-D SLAM for Differential Wheeled Robots
The study proposes a generative measurement model for encoders and derives the maximum a posteriori estimation expression and the Jacobians required for optimization, building a tightly coupled visual-inertial-encoder RGB-D SLAM system. On a self-built dataset, the system's real-time state estimation achieves a root mean square error of about 2-7 cm, used to compensate for the failure of pure vision solutions during temporary feature point loss and fast motion. The source code and the dataset containing encoder information have been made public.
arXiv cs.RO ·
- Higher-Order Kinematic Derivative Methods for Aspect-Preserving Real-Time Numerical Inverse Kinematics
The paper uses higher-order kinematic derivatives of serial robots to propose an aspect-preserving real-time numerical inverse kinematics method, yielding the QuIK4 and QuIK5 solvers with fourth- and fifth-order convergence. The method also includes an aspect-preserving step limiter that extrapolates the Jacobian determinant along the step to predict and avoid singularities, as well as a certifier that uses Hermite interpolation to verify the aspect of solutions and a certified restart algorithm. The authors claim the failure rate is reduced by up to four orders of magnitude compared with existing methods, and they release a C++ library with ROS 2 integration.
arXiv cs.RO ·
- When Architectural Spaces Begin to Act: How Architectural Robots Reshape Living and Spatial Control
Architectural robots, such as robotic partitions, ceilings, furniture, and facades, can move autonomously and reconfigure space. The author reflects on this: their impact goes beyond the moment of motion to include the spatial configurations that persist after motion stops. Such actions may benefit some occupants while disadvantaging others, and multiple robots together can make an entire architectural space appear to act. The author argues that understanding robotic architecture requires looking beyond short-term human-robot interaction to how people inhabit, negotiate, and retain control over autonomously reconfigurable spaces.
arXiv cs.RO ·
- Flexible Sensing Robot Manipulation: Deformation Estimation, Kinematics, and Control Based on Distributed Inertial Measurement
This paper proposes a flexible sensing manipulation framework that directly connects the structural dynamics of flexible links with sensing, kinematics, and control. The method first identifies the dominant vibration modes of each flexible link according to response convergence and excitation bandwidth criteria. Under the condition of full-rank modal observability, m retained modes require only m independent slope measurements and one reference IMU, and the continuous link deformation is reconstructed accordingly for flexible sensing forward kinematics and a PDE-based controller.
arXiv cs.RO ·
- Survey "When the Past Shapes Action" Reviews Requirements and Architectures of Embodied Memory
The arXiv paper "When the Past Shapes Action: Understanding Embodied Memory" defines embodied memory as the retention of decision-relevant information beyond the current observation, and organizes existing methods around six fundamental memory requirements and eight architectural categories.
arXiv cs.RO ·
- Study: Biomechanical metrics cannot predict perceptual and cognitive consequences of force augmentation
An arXiv study used an elbow-assist exosuit to examine the physiological, perceptual, and cognitive consequences of force augmentation during lifting, finding that although assistance reduced muscle activity, behavioral outcomes did not simply correspond to this biomechanical change. Assistance reduced perceived weight, but this effect was strongly shaped by participants' initial experience; assistance also selectively reduced adaptation to changes in environmental conditions, and differences in effort-based decisions were likewise shaped by initial experience rather than simply following the decline in muscle activity or perceived fatigue. The authors therefore argue that the perceptual and cognitive consequences of force augmentation cannot be inferred from biomechanical benefits alone and must be assessed alongside physical performance.
arXiv cs.RO ·
- Interaction-Aware Sampling-Based Motion Planning for Autonomous Surface Vessels in Urban Waterways
The authors propose a decentralized motion planner based on model predictive path integral control that jointly computes the ego vessel's trajectory and predictions of other vessels' trajectories, encoding traffic rules as discontinuous costs without requiring smooth approximations. In maps taken from real sections of Amsterdam's canals, 780 randomized runs all reached their goals without collisions or deadlocks, outperforming an optimization-based planner designed for the same domain as well as a version of the proposed planner that does not account for interaction. Two scaled vessel prototypes completed head-on and crossing encounters without rule violations, planning and localizing onboard at 10 Hz in an outdoor environment.
arXiv cs.RO ·
- OpenVIO: An Open-Source Visual-Inertial Odometry System
OpenVIO is a visual-inertial odometry (VIO) system released as open source under the MIT license. It supports pinhole and fisheye cameras and extends to stitched 360° images. The authors describe the design considerations for each module of the system and benchmark it against other open-source VIO systems on public datasets. The code is open source, and the paper is 7 pages with 6 figures.
arXiv cs.RO ·
- GPU-Accelerated Incremental Euclidean Distance Transform for Online Motion Planning of Mobile Robots
This paper proposes a voxel mapping system that uses parallel computing to simultaneously generate occupancy grid maps (OGMs) and Euclidean distance transforms (EDTs), and incrementally builds a global EDT to output high-frequency local distance information for online motion planning. The system uses GPU programming to compute EDT in parallel within local volumes, then continuously integrates new observations into the global EDT via a parallel wavefront algorithm while preserving historical observations.
arXiv cs.RO ·
- ResMerge: Residual Policy Learning and Merging for Continual Adaptation of Pre-trained Robot Policies
ResMerge proposes a two-stage framework that learns mergeable residual policies atop a frozen pre-trained policy: residual reinforcement learning obtains task-specific corrections during adaptation without additional expert demonstrations, while parameter-space merging consolidates compatible residuals to reduce stored parameters.
arXiv cs.RO ·
- ∇Mimic: Efficient Whole-Body Control for Humanoid Robots with Differentiable Simulation
The authors propose ∇Mimic, which uses exact gradients from a differentiable simulator to train whole-body motion-tracking policies for humanoid robots, reaching a score of 0.82 in 20 minutes and 0.874 in 1.8 hours on a single GPU, whereas the world-model method takes 1.2 hours to reach 0.82.
The paper presents a complete scheme for training humanoid policies with exact gradients under differentiable simulation and open-sources the engine and code, making it easy to compare the efficiency of first-order and zeroth-order methods.
arXiv cs.RO ·
- DMAT: Direct Action-Manifold Modeling for Efficient and Robust Bimanual Manipulation
The authors propose the Direct Manifold Action Transformer (DMAT), which reframes bimanual action generation as directly modeling clean, observation-conditioned joint-space action chunks from stochastic interpolants, enabling single-step inference without iterative denoising or trajectory straightening.
arXiv cs.RO ·
- RTPolicy: Real-time multi-view visuomotor policy for edge devices, inference at 32.9 Hz
RTPolicy is a multi-view visuomotor policy that uses view-aware feature fusion and visual compression to aggregate multi-camera information into a compact token representation, and uses a flow-matching action generator to reduce action-generation overhead. On the 50 tasks of the RoboTwin 2.0 single-task clean evaluation, it achieved an average success rate of 52.26%, higher than the strongest leaderboard baseline π0 at 46.4%.
arXiv cs.RO ·
- VLA policies still start executing without instructions: research on unintended task execution and start suppression
The study applied five types of instructions—empty, neutral, meaningless, infeasible, and wrong-task—to six model checkpoints in the LIBERO-Goal simulation, holding the initial state fixed and varying only the instruction, to examine whether the VLA policy starts, which task it completes, and what the instruction determines.
arXiv cs.RO ·
- Study provides complete analytical characterization of optimal collision-free motion for two robots
The paper derives a complete analytical characterization of optimal collision-free trajectories for two robots moving from rest to rest under double-integrator dynamics and a squared-acceleration objective. It proves that these trajectories belong to eight contact families and gives the family determination for each combination of initial and final positions. The authors analyze the geometric properties of the optimal trajectories, provide a numerical computation algorithm, and discuss how these results can improve the performance of existing numerical trajectory optimizers.
arXiv cs.RO ·
- SCI: A Contact-Based Optimization Method for Collision-Free Motion Planning for a Million Robots
The authors propose the sequential contact insertion (SCI) algorithm, which organizes optimization around contact points where robots reach the minimum allowed separation and analytically reconstructs trajectories between contacts. In numerical experiments, the method can plan for one million robots within minutes, while thousands of robots take less than one second; on problems solvable by a fixed-grid sequential convex programming baseline, SCI achieves median speedups of several orders of magnitude with comparable solution accuracy.
arXiv cs.RO ·
- AC-SMPC: Differentiable Actor-Critic MPC with State Constraints for Safe and Fast Robot Navigation
The authors propose AC-SMPC, an actor-critic model predictive control framework with state constraints for safe navigation in constrained dynamic environments. The method represents the robot and obstacles as vertices and the workspace as half-spaces, locally linearizes the nonlinear dynamics, and convexifies hyperplane-based collision avoidance constraints into a differentiable MPC layer; the actor adjusts MPC objective parameters via closed-loop feedback, while the critic evaluates long-term task performance.
arXiv cs.RO ·
- SAFARI: Semantic- and Frontier-Driven Autonomous Risk Inspection Framework
SAFARI treats object detection as a native channel of a unified probabilistic map, letting geometric and semantic evidence jointly drive exploration and planning. The authors completed 11 missions on a quadruped platform across three field sites, achieving an average coverage of 98.7% of the accessible mission area, with 97.6% of mission time requiring no operator intervention, and detecting objects with characteristic dimensions as small as 15 cm. Ablation experiments show that object-size awareness and safety-aware path planning are critical for hazardous-object search.
arXiv cs.RO ·
- Physically Constrained Kinematic Calibration for High-Precision Robotic Needle Guidance
The paper proposes a bound-constrained kinematic calibration method to improve the positioning accuracy of a 6-DoF robotic needle-guidance manipulator. The method constrains a 19-parameter geometric identification model with physically plausible parameter ranges, treating the bounds as active optimization constraints to mitigate parameter coupling and overfitting. In simulation, end-effector RMSE dropped from 3.422 mm to 0.690 mm (a 79.8% improvement); in benchtop experiments, trajectory validation RMSE was 0.865 mm and coordinate grid validation RMSE was 0.610 mm.
arXiv cs.RO ·
- BioAgent: An embodied agent that autonomously acquires skills and expands capabilities for long-horizon laboratory protocols
BioAgent is an embodied agent for long-horizon laboratory protocols that acquires new skills by matching human-reviewed requirements with validated skills, selecting tool-based implementations for missing behaviors, and requesting human demonstrations as needed. On the second task, it reused 17 skills unchanged, modified 2 existing implementations, and added 5 new skill types; on two dual-arm laboratory tasks with 20 and 31 ordered skill invocations respectively, it achieved complete-task success rates of 66% and 58%, with each task run 50 times and autonomous recovery enabled.
arXiv cs.RO ·
- MolmoSpaces-CommonSense: A Commonsense Reasoning Benchmark for Evaluating Robotic Manipulation Policies
The authors propose the MolmoSpaces-CommonSense benchmark, which builds a reasoning taxonomy grounded in developmental cognitive science and examines commonsense reasoning about occlusion, containment, support relations, semantically correct grasp points, spatial affordances, and hidden objects.
arXiv cs.RO ·