A humanoid robot being escorted away by police in Macau has gone viral online, prompting jokes about what some called the world’s first “robot arrest.”
Updated
March 13, 2026 2:04 PM
Macau police officer accompanying the humanoid robot. PHOTO: THREADS@BOXOF_CHOCOLATE
Police in Macau recently detained a humanoid robot after it frightened an elderly woman on a public street. The unusual encounter quickly spread online, prompting jokes about what some called the world’s first “robot arrest”.
On the evening of March 5, the robot was taken away by officers after the encounter triggered alarm among bystanders. Videos circulating on social media show an elderly woman confronting the robot on a sidewalk, visibly distressed and shouting that her “heart is pounding” while demanding to know why such “nonsense” was happening on the street. In the clip, the robot raises both hands toward the woman after she lashes out in fear — a gesture many viewers interpreted as a sign of apology.
Shortly afterwards, two officers from the Macau Public Security Police Force were seen escorting the robot and a man believed to be its operator away from the area. An officer is seen placing his right hand on the robot’s shoulder — the same posture police often use when presenting arrested suspects in official photographs.
That scene quickly spread online, fuelling jokes about what some called the world’s first “robot arrest”.
Photos shared online show a humanoid robot with long limbs and exposed mechanical joints, built from a black metallic frame without an outer shell. In dim lighting, several commenters said it resembled a “moving skeleton” — a striking sight for pedestrians encountering it unexpectedly on the street.
Witnesses said the woman appeared severely shaken and an ambulance was eventually called to take her to the hospital.
The incident also sparked discussion online about robots operating in public spaces. Some commenters argued that experimental technologies should be tested in controlled environments, while others said machines moving through public areas should have clearer designs or safety measures to avoid alarming pedestrians.
It remains unclear who deployed the robot or what purpose it was serving in the area at the time of the incident. Authorities have not released further details about the device or whether any action was taken following the encounter.
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A new safety layer aims to help robots sense people in real time without slowing production
Updated
February 13, 2026 10:44 AM
An industrial robot in a factory. PHOTO: UNSPLASH
Algorized has raised US$13 million in a Series A round to advance its AI-powered safety and sensing technology for factories and warehouses. The California- and Switzerland-based robotics startup says the funding will help expand a system designed to transform how robots interact with people. The round was led by Run Ventures, with participation from the Amazon Industrial Innovation Fund and Acrobator Ventures, alongside continued backing from existing investors.
At its core, Algorized is building what it calls an intelligence layer for “physical AI” — industrial robots and autonomous machines that function in real-world settings such as factories and warehouses. While generative AI has transformed software and digital workflows, bringing AI into physical environments presents a different challenge. In these settings, machines must not only complete tasks efficiently but also move safely around human workers.
This is where a clear gap exists. Today, most industrial robots rely on camera-based monitoring systems or predefined safety zones. For instance, when a worker steps into a marked area near a robotic arm, the system is programmed to slow down or stop the machine completely. This approach reduces the risk of accidents. However, it also means production lines can pause frequently, even when there is no immediate danger. In high-speed manufacturing environments, those repeated slowdowns can add up to significant productivity losses.
Algorized’s technology is designed to reduce that trade-off between safety and efficiency. Instead of relying solely on cameras, the company utilizes wireless signals — including Ultra-Wideband (UWB), mmWave, and Wi-Fi — to detect movement and human presence. By analysing small changes in these radio signals, the system can detect motion and breathing patterns in a space. This helps machines determine where people are and how they are moving, even in conditions where cameras may struggle, such as poor lighting, dust or visual obstruction.
Importantly, this data is processed locally at the facility itself — not sent to a remote cloud server for analysis. In practical terms, this means decisions are made on-site, within milliseconds. Reducing this delay, or latency, allows robots to adjust their movements immediately instead of defaulting to a full stop. The aim is to create machines that can respond smoothly and continuously, rather than reacting in a binary stop-or-go manner.
With the new funding, Algorized plans to scale commercial deployments of its platform, known as the Predictive Safety Engine. The company will also invest in refining its intent-recognition models, which are designed to anticipate how humans are likely to move within a workspace. In parallel, it intends to expand its engineering and support teams across Europe and the United States. These efforts build on earlier public demonstrations and ongoing collaborations with manufacturing partners, particularly in the automotive and industrial sectors.
For investors, the appeal goes beyond safety compliance. As factories become more automated, even small improvements in uptime and workflow continuity can translate into meaningful financial gains. Because Algorized’s system works with existing wireless infrastructure, manufacturers may be able to upgrade machine awareness without overhauling their entire hardware setup.
More broadly, the company is addressing a structural limitation in industrial automation. Robotics has advanced rapidly in precision and power, yet human-robot collaboration is still governed by rigid safety systems that prioritise stopping over adapting. By combining wireless sensing with edge-based AI models, Algorized is attempting to give machines a more continuous awareness of their surroundings from the start.