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#Safety and reliability
Oct 28Wed
  1. Reddit r/robotics58

    Robot lamp Lamp announces October development progress: 4,092 commits on main branch, new development docs and per-skill camera permissions

    Robot lamp Lamp announced its October development progress: the main development branch has already seen 4,092 commits this month, surpassing the previous high of 1,615 in April. The project added a docs/develop.md development path that takes about 10 minutes to get started, including a simulated lamp on a laptop, Python and JavaScript SDKs, and lamp-mcp; camera images are now authorized separately per skill, and a yield detection based on servo position and load was added, with this feature off by default.

  2. 爱范儿58

    Vine-inspired soft robotic intubation system SRIS achieves 87% first-attempt success rate in cadaver tests

    A team led by Elliot Hawkes at Stanford University designed the soft robotic intubation system SRIS based on the vine robot principle. In cadaver tests, 12 participants, including 8 emergency responders, received 5 minutes of training; 87% achieved successful intubation on the first attempt, with an average time of 21 seconds. Under the same conditions, video laryngoscopy had a 63% success rate and an average time of 44 seconds.

  3. OFweek Robotics40

    The Regulatory Blind Spots Behind the World's First Robot Molestation Case

    Outside a fast-food restaurant in Cologne, Germany, a 16-year-old girl was touched on the buttocks from behind by a 1.2-meter-tall humanoid robot styled as Iron Man; two young people (the robot's 16-year-old owner and his 19-year-old companion) livestreamed the entire incident from nearby, and police opened an investigation on suspicion of sexual insult and seized the robot and two mobile phones from a car trunk nearby.

  5. arXiv cs.RO50

    Constraining World-Model Planning with Legal Reasoning: Validation of a Defeasible Deontic Logic Planning Stack on a Simulated Robotic Arm

    The paper proposes a legal planning stack that uses Defeasible Deontic Logic (DDL) to constrain a motion planner, leveraging a learned world model for planning and to supply legal context, thereby enabling ex ante intervention before an illegal action is executed. The stack was deployed in a scenario where a simulated robotic arm pushes blocks on a 3x3 grid. Results show that the legally constrained agent complied with norms at a markedly higher rate than the unconstrained one, and that modeling perceptual uncertainty further raised the compliance rate; legal reasoning ran efficiently at runtime, its rulings were auditable, and the stack adapted to exogenous signals and endogenous rule changes.

  6. arXiv cs.RO65

    Gradient-Free Neural Hamilton-Jacobi Reachability for Scalable Safety-Critical Control

    The authors propose a discrete-time neural reachability framework that learns backward reachable tubes (BRTs) and backward reach-avoid tubes (BRATs) through Bellman-Isaacs value propagation, and uses gradient-free value probes to construct approximate teacher actions, turning adversarial actor learning into supervised policy learning.

  9. arXiv cs.RO75

    In-hand object pose reaching strategy and safety filter for the LEAP dexterous hand

    The research team proposed a training recipe for in-hand object pose reaching with the LEAP dexterous hand. It trains in simulation without human data and, after system identification, transfers zero-shot to the real robot, using either motion capture or a single wrist-mounted monocular depth camera. In a real-robot evaluation with 4 objects and 4,800 unseen targets over 13.3 hours, the state-based policy reached 95.2% of targets within 2 cm and 0.4 rad; adding a learned residual safety filter with adjustable conservativeness reduced drops by 75% while still reaching 91.5% of targets.

  10. arXiv cs.RO58

    Non-line-of-sight passive object sensing using distributed sensing and hyperdimensional computing

    The paper proposes a framework that relies solely on distributed channel measurements from communication infrastructure to sense passive entities outside a robot's field of view and perform risk-aware classification. The method uses hyperdimensional computing (HDC) to embed measurements into high-dimensional representations without explicit channel reconstruction. Numerical simulations based on commercial ray tracing and validation in a ROS smart factory scenario show accuracy of up to 89% under severe occlusion while maintaining low computational complexity.

  11. arXiv cs.RO62

    VLA-Stem: Adding a Lightweight Safety Mechanism to Vision-Language-Action Models with Reinforcement Learning

    Researchers propose VLA-Stem, a lightweight reinforcement-learning-based safety mechanism that does not fine-tune the underlying VLA policy; instead, it converts its action chunks into motion references and, at inference time, adaptively corrects execution using proprioception and local obstacle information. Across six constrained simulation settings, VLA-Stem achieved an average collision-free task success rate of 52.8%, versus 23.7% for the strongest safety baseline, while preserving the original policy's performance in obstacle-free environments; real-robot experiments also showed reduced collisions under static and dynamic obstacles.

  12. arXiv cs.RO57

    KEPT: Conformal Prediction Keepout Planning for Enclosed-Space Navigation Under Degraded Sensing

    KEPT proposes a navigation method for enclosed spaces such as tunnels and mines, using conformal prediction to calibrate keepouts around mapped walls under degraded sensing, and adjusting the margin according to a label-free degradation severity estimate to maintain coverage. The planning and control layer enforces a braking-distance condition on the keepout at plan time and on every command, using the measured tracking residual as its only margin and never altering the keepout.

  13. arXiv cs.RO64

    Omni-IGN: Omnidirectional Vision Onboard Image-Goal Navigation System for Drones

    The authors propose Omni-IGN, a fully onboard drone image-goal navigation (ImageNav) system that integrates quad-fisheye perception, an attention-based reinforcement learning policy, and a collision-aware safety layer. The policy adaptively fuses goal-relevant features across multiple views to provide directional guidance for continuous navigation, and the quad-fisheye RGB images support both ImageNav and obstacle avoidance without a dedicated depth sensor.

  14. arXiv cs.RO56

    When Black-Box Robot Policies Fail: Online Sensor Diagnosis and Repair with a Transparent Surrogate

    The study proposes a structured surrogate model that separates periodic gait from sensor-dependent correction terms, diagnosing and repairing corrupted inputs externally around a frozen locomotion policy. On simulated Go2, offline diagnosis raises walking success from 259/640 to 429/640, while online repair reaches 382/640, with no repair triggered in 64 held-out fault-free episodes. The authors note that the evidence remains limited to a single policy and a partly screened simulated fault set, and that robot foundation model and hardware validation have not yet been conducted.

  15. arXiv cs.RO58

    An Auditable Framework for Autonomous Driving Laboratories: LAM, OpenSDL, Safe-SDL, and L3-Bench

    The authors propose a traceable framework comprising four components—LAM, OpenSDL, Safe-SDL, and L3-Bench—to connect experiment planning, automated execution, and measurement feedback. LAM is a measurement-conditioned policy architecture that extends the vision-language-action paradigm to generate both continuous robot trajectories and typed instrument API calls; OpenSDL maps role-level operations to heterogeneous devices and records timestamped causal events.

  16. arXiv cs.RO55

    Program-Level Adversarial Co-Adaptive Self-Play for Robot Security

    The paper proposes a program-level adversarial co-adaptive self-play framework that lets coding agents generate attacks and defenses based on opponent code and task feedback, without model fine-tuning. The framework provides external program interfaces for autonomous driving and SDK-level defense interfaces for humanoid robot locomotion; two eight-generation case studies show that the driving defender introduced direct-actuation recovery, while the humanoid defender revised incoming-state validation. These responses provided only local task recovery and did not establish sustained robustness.

  17. IEEE Spectrum Robotics40

    VicOne LAB R7 Study: Are Robot Safety Functions Still Reliable When Inputs Are Tampered With?

    VicOne LAB R7 testing shows that tampered inputs can make robots respond normally as designed while taking wrong actions: a robot dog treated poster text as instructions and changed its movement; in a hospital service robot simulation, ultrasound-band audio altered behavior; and ROS 2/DDS message injection made a robot that should have stayed still move.

Oct 27Tue
  1. The Robot Report71

    ANYbotics begins delivery of explosion-proof quadruped robot ANYmal X

    ANYbotics has launched and begun delivering the quadruped inspection robot ANYmal X, which it calls the first legged inspection robot for explosive environments, compliant with European ATEX and global IECEx standards. Aimed at oil and gas and chemical scenarios, the robot uses explosion-proof enclosures for its 12 leg actuators and battery, places its AI computer and inspection equipment in a nitrogen-filled sealed compartment, and includes protections such as grounding and automatic temperature cutoff.

  2. 机器之心 · 微信公众号58

    UIUC, Google, Stanford and others jointly review how Proactive AI can move toward superintelligent agents

    Researchers from UIUC, Google, Stanford, UC Berkeley and CMU jointly published the review "Proactive AI for Superintelligent Agents," systematically mapping the research landscape of proactive AI and proposing a 6A framework composed of six capabilities: Awareness, Anticipation, Agenda, Arbitration, Action and Adaptation.

  3. 脑极体 · 微信公众号38

    World's first robot molestation case: the regulatory blind spots behind a 16-year-old girl's assault by a humanoid robot in Cologne

    Late at night on October 11, a 16-year-old girl outside a fast-food restaurant in Cologne, Germany, was touched on the buttocks from behind by a 1.2-meter-tall Iron Man-shaped humanoid robot that also made sexually suggestive movements; two young people livestreamed the entire incident, and police found the robot and two mobile phones in the trunk of a nearby car, investigating the robot's 16-year-old owner and his 19-year-old companion on suspicion of sexual insult.

  4. 钛媒体18

    Why the wealthy buy security robots first, seen through humanoid robots that can fight

    In a 61-second video, a silver-white humanoid robot sprints and flips onto a car roof, dents the door with a knee strike, and smashes the hood with an elbow, then stands between a knife-wielding person and a woman in broad daylight. Drawing on Douglas Rushkoff's "Survival of the Richest," in which the wealthy ask how to maintain authority over a security force after a major event, the article argues that security humanoid robots will first serve high-purchasing-power groups, that being able to fight shows they will not betray their owners, and that they are an invisible status symbol.

  6. arXiv cs.RO62

    SentryVLA: Uncertainty-Guided Action Selection and State Monitoring for Vision-Language-Action Robotic Control

    SentryVLA is a lightweight runtime wrapper for frozen VLA policies that requires no retraining or changes to the model architecture. At the action level, it uses conformal quantile regression to estimate an upper bound on the deviation between sampled actions and expert behavior, and ranks multiple stochastic candidate actions accordingly; at the execution level, it uses a Mahalanobis-distance anomaly score to monitor abnormal states during closed-loop control. Simulation and real-world experiments show that the method improves action selection and provides useful runtime warning signals.

  7. arXiv cs.RO71

    Guardian: Detecting Robotic Planning and Execution Errors with Vision-Language Models

    The study proposes an automatic framework for generating robotic planning and execution failure data, builds the GuardianFail-36k failure reasoning dataset based on RLBench and BridgeDataV2, and trains Guardian, a multi-view reasoning vision-language model. Guardian achieves state-of-the-art performance on three unseen real-world benchmarks: RoboFail, RoboVQA, and the newly introduced UR5-Fail. When combined with LLM-based manipulation policies, it improves task success rates in both simulation and real-world deployment. Code, data, and models are publicly available.

  8. arXiv cs.RO62

    IndustryNav: Evaluating Spatial Reasoning and Safety of Embodied Agents in Dynamic Industrial Navigation

    The authors propose IndustryNav, a simulation environment with 24 warehouse scenes for closed-loop navigation to specified destinations, and introduce safety metrics that record collisions and near-collision warnings. Experiments with 11 leading open- and closed-source VLLMs and 3 navigation baselines show that agents can reach their goals yet collide with moving obstacles, exposing a gap between task success and safe navigation.

  9. arXiv cs.RO52

    Uncertainty Evaluation for SOTIF Analysis of ML LiDAR Object Detection: Transfer Testing of Performance Targets

    The paper proposes an uncertainty evaluation method for ISO 21448 SOTIF analysis: an uncertainty threshold selected under one condition is transferred to a triggering condition, and a test decides at a given error probability whether the performance target is applicable, not applicable, or undetermined under that condition, and provides a lower bound on the number of independent units required for an applicable conclusion.

  12. arXiv cs.RO34

    PARS: Post-Quantum IoT Blockchain Security for Mission-Critical Physical AI Agents

    Addressing the threat quantum computers pose to public-key authentication and key agreement, the study proposes the "rotational secrecy" architectural objective and the PARS reference mechanism, which coordinates policy-triggered key establishment, rotation, and reconciliation among authorized Physical AI agents. The optional PARS-ESL permissioned chain, maintained by authorized validators or edge gateways, records only authentication state such as key epochs, group membership, revocation, and algorithm-suite policies, not high-frequency business transactions, allowing resource-constrained agents to join as lightweight clients.

  13. arXiv cs.RO40

    Contract-Based Agentic Systems Engineering: Using Quotient Operations to Achieve Assured System Design

    The study proposes treating SysML v2 requirements with assumptions and required constraints as assume/guarantee contracts. After decomposing system requirements over fixed neighbors, the weakest sound requirement for an open component is the contract quotient, which can be expressed in Signal Temporal Logic.

  14. arXiv cs.RO62

    Continuous-Time Safe Planning and Control for Agile Quadrupeds

    The research proposes a real-time motion planning framework that retains the full SE(2) model of a quadruped robot along with its anisotropic, heading-coupled velocity constraints, and accepts the resulting nonconvexity. The method parameterizes trajectories as composite Bernstein polynomials, uses the convex hull property to prove that obstacle avoidance and input constraints hold throughout the entire planning horizon, and runs in closed loop at online replanning rates, sending body velocities to the motion controller.

  15. arXiv cs.RO58

    Distributed Predictive Flocking Control for a Swarm of Miniature Vibration-Driven Robots in a Confined Arena

    The study proposes a distributed predictive flocking controller in which each miniature vibration-driven robot independently solves a nonlinear model predictive control (NMPC) problem and exchanges only predicted trajectories with local neighbors, comparing six barrier and control barrier function (CBF) safety formulations on a digital twin of an open-source vibration-driven bristlebot in a 0.64-square-meter arena.

  16. arXiv cs.RO58

    Multi-Candidate Simplex Architecture: From Design-Time Identification to Runtime Construction of Context-Dependent Safe Regions of Attraction

    The study proposes a two-stage Region of Attraction (RoA) certification procedure: contraction-based stability analysis first determines a target set, which Taylor-model reachability analysis then verifies, thereby constructing a context-dependent safe RoA at runtime and enabling safe switching among high-assurance controller candidates.

  17. arXiv cs.RO59

    Quantile-Based Command-Reserve MPC for Current-Command Gimbal Pointing Control

    This paper studies line-of-sight pointing control for a two-axis current-command gimbal under mismatched mechanical disturbances. It proposes a quantile disturbance predictor and a tube-inspired model predictive controller that reserves command headroom according to prediction uncertainty. On a two-axis embedded platform, the proposed configuration achieved a 2D pointing RMS error of 3.94 ± 0.10 mrad, with no command-saturation samples within the evaluation window; solve times and cycle overrun records are reported separately for a 100 Hz nominal implementation.

  18. 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.

  19. arXiv cs.RO58

    Review: Communication, Coordination, Collaboration, and Social Interaction in Networked Humanoid Robots

    This 35-page review divides networked humanoid robot intelligence into four functional categories based on information exchange: communication, coordination, collaboration, and social interaction with humans. It surveys the literature along six dimensions: interaction architecture, exchanged information, physical coupling, timescale, system scale, and embodiment.

  20. 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.

  21. arXiv cs.RO60

    Dream2Assist: Intent-Conditioned World Models for Shared Vehicle Control

    The authors propose Dream2Assist, a model-based reinforcement learning framework that adds intent inference to a recurrent state-space world model, enabling an assistive policy to anticipate and support discrete human goals without taking over human control. The work also presents a complete deployment pipeline from world-model policy to a safe human-machine system, addressing the sim-to-real-human gap through policy down-selection and reward restructuring, and validates it in two human-subjects studies, high-speed racing (N=30) and urban driving (N=10), plus a preliminary on-vehicle deployment, where intent conditioning produced measurable improvements in torque alignment and collision rate.

  22. 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.

  23. arXiv cs.RO58

    Sybil-Resilient Multi-Drone Exploration of Indoor and Confined Spaces

    The paper studies the problem of Sybil attacks during multi-drone collaborative exploration of buildings: a compromised drone forges identities, claims frontiers, and sends fabricated scans, causing real drones to miss areas and generating nonexistent walls in the map. The authors propose five defenses that rely only on the drones' own sensors and maps, including auditing map data, checking for a body's presence at an identity's claimed location, trusting only identities whose bodies have been observed, quarantining identities unobserved by any drone, and binding each observed body to a single identity.