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#Perception and localization
Oct 27Tue
  1. arXiv cs.RO62

    GEMS: A Long-Term Spatiotemporal Memory Framework Combining 3D Gaussian Splatting Maps with Agentic Reasoning

    The authors propose the GEMS framework, which combines a persistent spatiotemporal 3D Gaussian Splatting (3DGS) map with an agentic reasoning pipeline. The map is reconstructed once and thereafter updated only in regions where the scene changes, with those modifications saved. Using this map, the agentic pipeline renders novel views on demand, progressively accumulates evidence to answer spatiotemporal questions, and grounds objects from natural-language queries.

  2. arXiv cs.RO60

    TrySee: Modular Perception-Enhanced VLM Closed-Loop Robot Task Planning for Specialized Domains

    TrySee proposes a modular closed-loop robot task planning pipeline that combines general-purpose VLM reasoning with domain-specific perception and existing robotics components, without requiring VLM fine-tuning or end-to-end demonstrations. The system uses reactive cyclic planning and adds domain-specific modular vision preprocessing to provide online grounding, while a dynamic preprocessing selection mechanism improves scalability.

  3. arXiv cs.RO62

    VPR-Space: A Benchmark for Visual Place Recognition in Space Analog Domains

    The paper proposes the VPR-Space benchmark to evaluate visual place recognition (VPR) capabilities in extraterrestrial surface scenarios such as the Moon and Mars. The authors built 16 database-query datasets based on existing data from Space Analog Domains (SAD), covering challenges including environment, viewpoint change, and illumination conditions.

  5. arXiv cs.RO59

    LRIO: Resilient Decentralized Radar-LiDAR-Inertial Odometry for Subterranean Environments

    The authors propose LRIO, a decentralized LiDAR-radar-inertial odometry framework that fuses LiDAR, FMCW radar, and inertial sensing for pose estimation in GPS-denied subterranean tunnels affected by smoke. At the core of the framework is an Adaptive Residual Thresholding (ART) mechanism, which detects sensor degradation over time and adjusts the fusion process, combined with a Robust Error-Tolerant Optimal Information Filter (RETOIF) that fuses LiDAR-inertial and multiple radar-inertial odometry estimates in a fault-aware manner.

  6. arXiv cs.RO58

    VisGeo-PipeTrack: A visual-geometric servo control framework for UAV dynamic pipe tracking

    The paper proposes the VisGeo-PipeTrack servo control framework, which uses YOLOv5 to detect pipe labels and combines visual geometric constraints for localization, enabling UAVs to track pipes with dynamic motion such as vibration. On the control side, it adopts a model predictive control-based real-time corrected adaptive PID (MPC-RCAPID), which estimates the model online via recursive least squares and adjusts PID parameters through rolling optimization.

  8. arXiv cs.RO55

    Factor-Graph-Based 3D Force Estimation for Dual-Arm Manipulation of Flexible Cables

    This study proposes using factor graphs to probabilistically model deformable linear objects (DLOs), estimating the magnitude, direction, and location of 3D forces acting on them while simultaneously reconstructing the cable's shape. Because cables are thin and unactuated, strain gauges and actuation readings are generally impractical; the method uses only one type of sensing information and performs force estimation in simulation tests that add measurement noise and have the cable move along a prescribed path. The authors state that this general method can apply to a broader range of tasks.

  9. arXiv cs.RO58

    MMGNet: A Multimodal 6-DoF Grasp Synthesis Network for Cluttered Scenes

    MMGNet proposes a multimodal grasp synthesis network that uses hierarchical image-to-3D feature injection and rotational graspness modeling to integrate multi-scale image features into 3D representations and jointly predict grasp approach direction and in-plane rotation. On GraspNet-1Billion with RealSense data, it achieves a mean AP of 60.34, surpassing all compared methods; in real-world experiments with adversarial grasp objects, its grasp success rate is 8.46 percentage points higher than AnyGrasp. Ablation studies show that the two modules provide complementary gains. Code, models, and data will be released after the paper is published.

  10. arXiv cs.RO60

    Localization-Uncertainty-Aware UAV Swarm Search for GNSS-Denied Maritime Surveillance

    The paper proposes an uncertainty-aware control barrier function (CBF) framework that approximates cascading covariance along multi-hop localization chains using Fisher information matrices, for UAV swarm search in GNSS-denied maritime environments. The framework incorporates the covariance model and its rate of change into constraint margins for connectivity maintenance and collision avoidance, and combines a hierarchical Voronoi target strategy with formation keeping to achieve forward coverage.

  11. arXiv cs.RO66

    ISB-NMPC: Spherical-Bearing Nonlinear Model Predictive Control for Quadrotor Interception

    The authors propose ISB-NMPC, which couples spherical-bearing prediction with nonlinear quadrotor dynamics to jointly optimize target-approach motion and target visibility. Across 30 paired simulation trials, the method achieved an interception success rate of 86.7%, the highest among the compared controllers, with a mean per-trial target-visible time of 99.11%. In outdoor flights, the interceptor acquired a 30 cm target at approximately 150 m, reached 17 m/s in long-range flight, and flew at approximately 14 m/s while pursuing a maneuvering target towed by a quadrotor. Both software and hardware are open source.

  12. arXiv cs.RO60

    OSMA-Bench: Evaluating Safety Under Obstacle Conditions in Household Robot Navigation

    The authors propose OSMA-Bench, a benchmark that uses spatially matched scenario sets differing only in obstacle type to test whether robot navigation adjusts clearance and speed according to obstacle semantics, and they propose the Semantic Sensitivity Index (SSI) to measure this adaptation. Evaluating VLM and vision-language-action (VLA) policies on the benchmark, they find that even with explicit safety prompts, neither consistently adjusts its motion according to obstacle safety levels.

  13. arXiv cs.RO43

    The German Tank Problem and Scent Navigation: Using a WWII Statistical Estimator to Determine Whether a Robot Has Reached an Odor Source

    Researchers borrow the serial-number estimation method from the WWII "German tank problem," treating a robot's chemical sensor readings as observation samples and using a running maximum and sample count to unbiasedly estimate the peak concentration of an odor plume, thereby determining the odor source location. The method provides exact confidence bounds that let a robot or UAV decide whether to keep searching or land, serving as a termination criterion for olfactory navigation. The paper derives the estimator and its confidence bounds, demonstrates its sample efficiency, and examines its robustness when its assumptions fail.

  14. arXiv cs.RO59

    Distributed Sensing and Adversarial Localization of Narrowband Acoustic Sources for Offshore Data Center Monitoring

    This technical report proposes an acoustic surveillance framework for localizing and tracking narrowband adversarial acoustic sources that threaten offshore data centers. To address aliased TDOA measurements and an ambiguous solution space under narrowband emissions and sparse sensors, it introduces a mobile receiver that temporarily forms anchor pairs with selected fixed receivers to constrain the feasible solution space. The two-stage pipeline first estimates the source's initial position using anchor constraints, then initializes a particle filter that jointly tracks source position and velocity. In Monte Carlo simulations, the localization success rate was 91%, and 9 of 10 open-water field trials achieved tracking errors below 2 meters.

  15. arXiv cs.RO60

    PS-DLO: A Property- and Spatially Aware Deformable Linear Object Manipulation Policy

    The authors propose PS-DLO, a deformable linear object (DLO) manipulation policy that combines object properties with spatial awareness. Through contrastive image-text learning, it maps initial observations to categorical descriptions of DLO properties, and uses SAM3 to extract mask-guided features from future observations, which are distilled into an action expert. On nine real-world tasks across single-arm and bimanual platforms, PS-DLO achieves an average success rate of 68.9%, 20.0 percentage points higher than the strongest baseline; in six of seven visual-shift conditions for butterfly-knot untying, its success rate exceeds the baseline.

  16. arXiv cs.RO55

    Semantic-Coupled Perception Framework for Autonomous Laparoscope Control

    This paper proposes a closed-loop autonomous laparoscope control framework that couples real-time surgical phase recognition with camera-motion-compensated visual perception, using phase dependencies among surgical entities to improve target state estimation under occlusion and entity overlap. Surgical phase recognition and target tracking were evaluated on benchmark datasets, and phantom experiments showed improved target visibility and task execution performance compared with fixed-field-of-view control. The paper was submitted to IEEE Robotics and Automation Letters (RA-L).

  17. arXiv cs.RO64

    Millimeter-Wave Radar Uses Doppler Information to Track Occluded Targets' Position and Velocity

    The authors propose a method that uses millimeter-wave radar Doppler information to track non-line-of-sight occluded targets, achieving 8.95 cm position error and 1.75 cm/s velocity error on held-out trajectories. The study also releases the first indoor non-line-of-sight radar dataset, containing 576 sequences totaling 720,856 frames and covering 12 trajectories with different speeds, starting positions, and material configurations. The method models non-line-of-sight tracking as continuous position-velocity estimation, uses a shared 3D encoder to process the full range-azimuth-Doppler representation, and estimates position and velocity separately through two recurrent branches before fusing them into motion-consistent trajectories.

  18. arXiv cs.RO59

    LiDAR-based GNN framework learns interaction-aware path corrections from unlabeled trajectories for construction robots

    The study proposes a real-time, LiDAR-only framework that learns interaction-aware path corrections from unlabeled demonstrations: constant-velocity extrapolation generates residual learning targets, a GNN models relationships among the robot, pedestrians, and goal context, and at deployment an extended Kalman filter tracks LiDAR detections to build dynamic graphs, with the GNN offsetting planner-generated waypoints through a planner-agnostic interface.

  20. arXiv cs.RO58

    T-ConSG: A LiDAR-Based Real-Time Temporal Scene Graph for Dynamic Construction Environments

    The paper proposes T-ConSG, a LiDAR-based real-time temporal construction scene graph that uses spatial-relation edges and event-participation edges to jointly represent free space, static objects, dynamic objects, and environmental events. The framework incrementally builds the graph from LiDAR geometric evidence and explicitly represents changes in accumulated spatial evidence as installation and removal events. The authors validated the representation in three studies: dynamic-aware navigation on a bricklaying testbed, construction progress monitoring on the ConSLAM dataset, and online change detection in a simulated environment.

  21. arXiv cs.RO60

    Cut a Wall, See a Wall: Identity Substitution in Occluded Point-Cloud Perception for Construction Robots

    The paper finds that when entire regions of a scene are occluded at test time, point-cloud segmentation networks relabel the hidden elements into a single sink class; under fixed layouts this class absorbs up to 70% of test points, and baseline mIoU drops to 0.15-0.27. The authors append 14 hand-computed geometric features per point (GPE), restoring mIoU to 0.54-0.92 on PointNet++ and a PTv3-style transformer and removing 64-100% of whole-object losses; on real S3DIS scans, whole-wall losses drop from 10 to 0.

  22. arXiv cs.RO58

    A Motion-Induced WiFi-CSI Sensing Simulation Framework for Multi-Robot Systems

    This study proposes an open-source simulation framework that integrates the WiFi Sensor for Robotics (WSR) sensing pipeline into Gazebo. It can generate synthetic WiFi-CSI measurements with realistic physical signal characteristics and supports processing both simulated and real WiFi-CSI data for direct comparison and validation. The authors used TurtleBot3 robots to compare simulated and real experiments, demonstrating the framework's use in bearing estimation and robot localization. The code and experimental details have been made public.

  24. arXiv cs.RO60

    RoboReason: Improving robotics-relevant VLM reasoning with scalable data generation

    RoboReason proposes constructing spatial and temporal ordering tasks from real robot stereo camera and wrist camera images to evaluate the robotics-relevant reasoning capabilities of vision-language models; experiments show that several advanced VLMs perform poorly on the ordering tasks. The authors accordingly propose a scalable autonomous training data generation pipeline, and supervised fine-tuning and reinforcement learning on this data both significantly improve model performance on spatiotemporal ordering and downstream robotics and visual reasoning tasks. The work was accepted to the EMNLP 2026 main conference.

  25. arXiv cs.RO60

    POD-RoPE: Physical Observation Distribution Rotary Position Encoding for Embodied AI

    The authors propose POD-RoPE, which represents a token's observation footprint as a distribution over camera centers, viewing directions, and sampling times, uses expected rotations to encode relative relationships between distributions, and reduces to pointwise RoPE when each distribution collapses to a single point.

  26. arXiv cs.RO52

    Ground Friction Assessment Based on Robot Tire-Ground Interaction

    The study drove a skid-steer robot at set speed profiles over five surfaces with different friction characteristics, identifying surface type by the deviation between inertially estimated velocity and wheel odometry velocity. Response delay measurements showed a consistent surface-dependent trend, with the longest delay on soap and the shortest on carpet; spectral features achieved 97.1% balanced classification accuracy under record-level cross-validation. The authors conclude that both the magnitude of velocity mismatch and frequency-domain features contain tire-ground interaction information, which can be used for surface identification and for slip-aware wheel odometry weighting in state estimation.

  28. arXiv cs.RO62

    Keyframe Management for Dense Maps on Memory-Constrained Robots

    The authors propose a keyframe management method for dense maps on memory-constrained robots that directly limits the memory occupied by the resident map and admits and releases keyframes by semantic spatial units such as building rooms and corridors. Across every run on two NVIDIA Jetson boards, the memory budget was never exceeded and model throughput loss was at most 0.8%, whereas without the method the operating system terminates the model or the map. Under that budget, admission by semantic zone localized 6-9 percentage points more query frames than geometric partitioning by the number of matched regions, roughly twice that of RTAB-Map retrieval, with lower ATE.

  29. arXiv cs.RO62

    ReSight: Task-Driven Self-Improving Memory for Embodied Agents

    ReSight is a task-driven self-improving memory system for embodied agents that retains keyframes and their spatiotemporal associations, and separates observation evidence from extensible derived fields so that historical observations can be reprocessed for new needs. Through Explore-Distill-Mount (EDM), the system identifies capability gaps from execution and exploration records and converts exploration-derived solutions into reusable memory builders, query tools, and skills.

  31. arXiv cs.RO60

    Interpretable Collision Avoidance and Feasibility Guarantees via an Uncertainty-Aware Pipeline

    The study proposes a modular perception-prediction-planning pipeline that propagates uncertainty as structured, interpretable quantities across modules and guarantees a feasible solution in every cycle within convex safe sets. In Monte Carlo trials at a four-way unsignalized intersection, the pipeline achieved 0% collisions and 0% solver infeasibility, with 12.7 ms per cycle; the deterministic planner and chance-constrained baseline had collision rates of 36% and 10%, respectively. Ablation experiments confirmed the necessity of each uncertainty source, and a hardware deployment on a Clearpath Jackal UGV verified real-time feasibility.

  32. arXiv cs.RO62

    B-Adapt and BVSLAM: Adaptive Multi-Exposure Bracketing for More Robust Visual SLAM

    The authors propose B-Adapt and BVSLAM to address image saturation and lost visual correspondences in visual SLAM when automatic exposure fails to adjust in time under rapid illumination changes. B-Adapt captures adaptive exposure brackets to cover the scene's dynamic range while maintaining photometric overlap, and BVSLAM uses the multi-exposure sequence directly as constraints in factor-graph state estimation without relying on HDR merging.

  33. Guyuehome58

    Building a ROS LiDAR Map with an RK3588 Edge Computing Box: From Wiring to Saving the Map

    This article presents the complete process of deploying ROS LiDAR mapping on an RK3588 edge computing box, covering hardware wiring, system configuration, driver debugging, indoor data collection, and map saving. It also shares troubleshooting methods for common issues, aimed at helping beginners get started.

  34. Guyuehome42

    LANav in depth: when robots stop revisiting history and learn to organize memory

    LANav targets the open-vocabulary object goal navigation (OVON) task, in which a robot must find a target in an unfamiliar indoor environment using only its current first-person image. Its approach is to have the robot stop repeatedly reviewing past frames and instead organize its memory to support navigation decisions.

  35. New Strategy Robotics22

    Mech-Mind's "Eye-Brain-Hand" to Appear at Vietnam VIMF 2026, Demonstrating 7 Major Intelligent Applications for Precision Manufacturing

    Mech-Mind will exhibit seven "Eye-Brain-Hand" intelligent applications at VIMF 2026, held November 4-6 at the Kinh Bac Cultural Center in Bac Ninh Province, Vietnam. These cover high-precision assembly of FPC flexible flat cables, flexible picking and precision assembly of graphics card power cables, solder joint defect inspection for mobile phone flash units, appearance defect inspection for Type-C connectors, Pin measurement for automotive electronic connectors, screw height inspection for laptop cooling plates, and machine loading/unloading of high-reflectivity gears, targeting precision manufacturing scenarios such as 3C electronics, semiconductors, automotive electronics, and machining. Booth: Hall E, 350.

  36. OFweek Robotics58

    Shenmou Intelligent's "Dragon Claw" drone wins State Grid power aerial operations project

    Shenmou Intelligent's "Dragon Claw" aerial-operations drone has won State Grid Power's "High-Stability UAV for Aerial Operations" project, using a drone with a robotic arm and dexterous hand to clear foreign-object hazards on overhead transmission lines. The system identifies foreign objects such as bird nests through inspection, then uses the robotic arm and dexterous hand to handle and verify them, integrating detection, handling, and verification into one workflow. Shenmou says its core technologies include a self-developed flight control system, robotic arm and dexterous-hand grasping control, dynamic visual guidance, and piezoelectric six-axis force sensors, and cites research estimating annual procurement demand of about 150 million to 200 million yuan per province.

  40. Robotics & Automation News42

    Orbbec Gemini 330 Series: Active Stereo Cameras with Proprietary MX6800 ASIC Depth Processing

    All Orbbec Gemini 330 series active stereo cameras perform depth computation and depth-color alignment in-camera on the proprietary MX6800 depth engine ASIC, without using host computing power. Since launching the Gemini 335 and 335L in April 2024, the series has continued to expand, covering different baselines, optical filters, interfaces, and protection ratings.