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Only Opinion#Safety and reliability
TodayNov 11Wed1 updates
  1. The Robot Report22

    Why predictive maintenance matters more as factories add robots

    As factories deploy more robots, predictive maintenance uses equipment data such as vibration, temperature, motor current, torque, and controller alarms to identify early signs of wear in joints, reducers, motors, and controllers, so maintenance decisions are based on actual condition rather than a fixed schedule. IFR data shows that about 5 million industrial robots were in operation worldwide in 2025, up 11% year over year, and an unexpected failure of a single robot could affect an entire work cell and production line. Earlier warnings can reduce unplanned downtime, improve spare-parts planning, and make maintenance windows more controllable.

Nov 10Tue
  1. Robotics & Automation News31

    Opinion: Supervised autonomy in robotics must be designed for the robot's worst day

    Plus One Robotics CEO Erik Nieves argues that robots should be judged by their "worst day" rather than by smooth demonstrations, that is, by how they perform when facing situations they have never seen. The article advocates inventorying an exception list before deployment, defining the boundary between what the robot can handle on its own and what it must escalate, and having help requests carry information such as on-site images, number of attempts, and confidence. Nieves expects supervised autonomy to be the main shift in the next five years, and the ratio of supervisors to robots should be determined based on pilot data.

Nov 3Tue
  1. Robotics & Automation News22

    Opinion: What happens when the robot is wrong?

    Amid an accelerating automation trend with more than 5 million industrial robots in operation and the new ABB IRB 1700 model cutting cycle times by up to 20%, factories need to rehearse during commissioning how operators can safely question machine judgments. It is recommended to introduce three types of drills—false alarms, conflicting instructions, and shift handovers—and to record metrics such as challenge response time and decision arrival time. Safeguards, emergency stops, and risk assessments must still remain independent and take priority.

  2. 图灵人工智能 · 微信公众号40

    Tsinghua Professor Deng Zhidong: Physical AI Has Not Yet Had Its ChatGPT Moment; World Models Are Key

    Tsinghua University professor Deng Zhidong believes physical AI as a whole is still in an early exploratory stage and has not yet had its own ChatGPT moment; robots being able to run and dance does not mean they can enter homes to care for the elderly. He proposes that the key to a breakthrough lies in world models: letting AI rehearse consequences and costs before executing actions, combined with tasks and human intent, with evaluation criteria being generality, task success rate, and generalization ability. He also suggests connecting cloud, edge, and devices through mobile communications and deploying shared computing power at the edge to ease cost and power consumption pressures on device-side computing.

Oct 31Sat
  1. Reddit r/humanoidrobotics8

    Concept idea: Replace brain implants with an external head-mounted micro-drone companion controlled by remote or neural signals

    A user proposed an external head-mounted micro-drone companion concept, worn via a headband, hat, or frame, to avoid the surgical risks and approvals of brain-computer interface implants. The design uses ducted fans with safety mesh guards to protect hair, ears, and skin, and relies on proximity sensors and gyroscopes combined with AI to achieve stable hovering that moves with the head; control is via a small remote-control pad or surface neural/gesture signals. The poster asked the community about engineering and safety challenges such as battery weight, noise near the ears, and wind-disturbance stability.

Oct 27Tue
  1. 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.

Oct 23Fri
  1. Robotics & Automation News51

    Should inspection robots replace people or assist them? An engineer's two-year field review

    Daniela Shchegelskaya, an electronics and robotics engineer at Elimpus, shares two years of experience using Boston Dynamics' Spot for hazard-zone inspections in live power substations. She argues that robots should take on tasks such as carrying instruments into hazardous locations and providing more detailed viewpoints, keeping people away from danger while preserving key judgment.

Oct 22Thu
  1. 机器人全球资讯 · 微信公众号30

    Jensen Huang Praises OpenClaw for Advancing Robotics, Stresses Need for Proper Permission Controls

    NVIDIA CEO Jensen Huang said at the Build a Claw event in London that OpenClaw is one of the most important models to date, calling it "the first truly trustworthy agent runtime framework" and describing it as providing a real-time runtime framework for LLMs that can be used in robotics. He also stressed that autonomous systems must treat every object as untrusted by default and grant only minimum privileges, and introduced OpenShell, an isolation system NVIDIA developed for this purpose that continuously monitors for privilege violations and issues alerts.

Oct 16Fri
  1. Reddit r/humanoidrobotics22

    Opinion: VLA models alone cannot achieve safe humanoid robot deployment

    A Reddit user argues that vision-language-action (VLA) models alone are not enough to safely integrate humanoid robots into daily life. Humanoid robots far exceed humans in strength and speed; without complex multi-sensory input, learning from video by vision alone cannot master the human instinct to adjust force at the right moment in tasks such as holding a child's arm, carrying a cake, or closing a door, which can easily cause accidents and hinder the industry's adoption.

Oct 10Sat
  1. The Robot Report53

    TDK Ventures founder: dexterity is the real bottleneck for embodied intelligence

    TDK Ventures founder Nicolas Sauvage argues in an article that the key to robotic dexterity is not completing a single action, but the reliability of an entire workflow. He gives the example that when the single-step success rate is 99%, the probability of completing all 100 actions is only 36.6%, and only when it rises to 99.99% does it reach 99.0%.

Oct 8Thu
  1. Ars Technica49

    Nvidia bets on physical AI: Halos expands from autonomous driving to robot safety

    Nvidia is expanding its Halos operating system from autonomous driving to robotics, allowing developers to customize safety features without disrupting the underlying architecture. The system continuously monitors hardware and software libraries; Holoscan Sensor Bridge can be embedded in microcontrollers or FPGAs to identify corrupted sensor data. It also includes virtual environment simulation and an inspection lab program, providing safety feedback for robot development.

Oct 7Wed
Oct 1Thu
Sep 30Wed
Sep 28Mon
  1. Tsinghua Embodied Intelligence and Robotics Institute28

    Excerpt from Professor Zhang Tao's Lecture at the Tsinghua Humanities Forum: Embodied Intelligence Empowers Everything

    Professor Zhang Tao, Dean of Tsinghua University's Institute for Embodied Intelligence and Robotics, delivered a lecture titled "Embodied Intelligence Empowers Everything" at the Tsinghua Humanities Forum. He described three major characteristics of embodied intelligence—generality, interactivity, and autonomy—and noted that key technologies still need to be breakthroughs, including multimodal embodied large models, environmental perception, dynamic planning and control, and dexterous bodies.

Sep 15Tue
  1. Leiphone Robotics53

    Xspark AI's Ding Wenbo on tactile intelligence: Robots need their own "spinal cord"

    In an interview, Xspark AI co-founder and chief scientist Ding Wenbo proposed that vision has already solved about 99% of robot perception problems, and that touch should form a low-latency, body-adjacent "spinal cord"-level model rather than being directly integrated into vision large models. He proposed a three-layer architecture of "slow brain VLM—fast brain VTLA+TWAM—spinal cord VTA," arguing that touch mainly serves collision-avoidance safety and post-training for dexterous manipulation, and noted that current bottlenecks lie in sensor consistency, tactile data representation, and unification across sensors, modalities, and embodiments.

Jul 7Tue
Jun 30Tue
Feb 23Mon
  1. Dexterity37

    Dexterity explains why Physical AI is hard

    Physical AI—AI that drives robots to complete physical tasks in the real world—is hard because the physical world is endlessly variable: boxes deform and environments change from shift to shift. A truck-loading robot must simultaneously solve dozens of AI problems, including perception, planning, collision-free dual-arm motion, and force control, while achieving 99.9995% safety confidence for each action.