Medical robots, autonomous vehicles and other regulated robots

Some robots work in sectors that already had strong regulators long before robots arrived. Surgical and rehabilitation robots are medical devices, automated vehicles are motor vehicles, and drones are aircraft. In these sectors, a robot cannot simply be designed to a voluntary standard and sold; it needs authorization from a government regulator, or must meet mandatory federal standards, before it reaches users, and the manufacturer has continuing duties to report problems. These regimes are a preview of how other robots may be regulated as they become more autonomous. This lesson explains the medical device and motor vehicle frameworks in Canada and the United States, the emerging global framework for automated driving, and briefly how drones fit, with pointers to the courses that treat drones in depth.

Medical robots

Medical robots range from surgical systems, in which a surgeon at a console controls instruments inside a patient, to rehabilitation robots and exoskeletons used in therapy, pharmacy automation, radiotherapy positioning systems and hospital disinfection robots. Whether a robot is a medical device depends on its intended use: a device intended for diagnosing, treating, mitigating or preventing disease or injury, or for restoring or modifying body function, is a medical device, while a delivery robot that carries supplies in a hospital is not, even if it works next to patients.

In the United States, medical devices are regulated by the Food and Drug Administration (FDA) under the Federal Food, Drug, and Cosmetic Act. Devices are classified as class I, II or III by risk. Most class I and some class II devices are exempt from premarket review; most class II devices need premarket notification under section 510(k), which shows substantial equivalence to a legally marketed predicate device; novel low- to moderate-risk devices without a predicate can use the De Novo pathway; and class III devices need premarket approval (PMA) with clinical evidence. Robotically assisted surgical systems have generally reached the market through 510(k) clearance. Manufacturers must follow the Quality Management System Regulation, which aligned 21 CFR Part 820 with ISO 13485 from 2 February 2026, report deaths and serious injuries under the medical device reporting rules in 21 CFR Part 803, and meet cybersecurity requirements for connected devices added to the Act in 2022 as section 524B. FDA finalized guidance in December 2024 on predetermined change control plans for AI-enabled device software functions.

Medical robots also follow medical device standards that complement general machinery safety. IEC 60601-1 sets general requirements for basic safety and essential performance of medical electrical equipment, and its particular standards include IEC 80601-2-77 for robotically assisted surgical equipment and IEC 80601-2-78 for medical robots for rehabilitation, assessment, compensation or alleviation. ISO 14971 sets the risk management process for medical devices, playing the role ISO 12100 plays for machinery; IEC 62304 covers medical device software life cycles; and IEC 62366-1 covers usability engineering, which matters greatly for surgical consoles where a confusing interface can lead to harm.

The last row reflects a real difference in philosophy. A surgical robot carries risks to the patient that would be unacceptable for a factory machine, but they are judged against the benefit of surgery to that same patient. Researchers describe levels of autonomy for surgical robots, from no autonomy, where the surgeon controls every motion, through robot assistance and task autonomy, such as automated suturing, to conditional and high autonomy. Commercial systems are mostly at the lower levels at the time of writing, and regulators expect evidence that increases with autonomy.

Automated vehicles

An automated vehicle is a robot that carries people or goods on public roads. SAE J3016 defines six levels of driving automation, from level 0 (no automation) through level 2 (partial automation, where the driver must supervise continuously, as with most driver assistance systems) to level 3 (conditional automation, where the system drives in limited conditions but a human must take over when asked), level 4 (high automation within an operational design domain, with no takeover needed) and level 5 (full automation everywhere). The operational design domain describes the conditions, such as roads, speeds, weather and times of day, for which the system is designed, and defining it precisely is one of the most important safety decisions.

In the United States, the National Highway Traffic Safety Administration (NHTSA) regulates vehicle design through the Federal Motor Vehicle Safety Standards, which manufacturers self-certify, and through its defect and recall authority, while states regulate drivers, licensing, insurance, traffic laws and permits for testing and deployment, as California's DMV and Public Utilities Commission do for robotaxis. Vehicles without manual controls need exemptions from standards written for human drivers, and in April 2025 the Department of Transportation announced an automated vehicle framework that expanded an exemption program to domestically built vehicles. NHTSA's Standing General Order requires manufacturers and operators to report crashes involving automated driving systems and level 2 systems; an amended order took effect on 16 June 2025 with revised thresholds and timelines. Internationally, the UNECE adopted Global Technical Regulation No. 26 on automated driving systems in June 2026 with US co-sponsorship; how it will be reflected in US standards was under discussion at the time of writing.

Liability for automated vehicles is shifting from drivers toward manufacturers and operators. For level 2 systems, the driver remains responsible for supervising, but courts have also examined whether manufacturers' designs and marketing encouraged over-reliance; in 2025 a US federal jury in Florida found a carmaker partly liable for a fatal crash involving its driver assistance system, a verdict the company said it would appeal. For level 4 robotaxis with no driver, the operator is the natural defendant, and some jurisdictions have adopted rules making the automated system's owner responsible for traffic violations. Regulators have also used reporting duties: in 2024 one robotaxi operator paid a federal penalty for failing to fully report a 2023 crash in which its vehicle dragged a pedestrian.

# How many driverless miles are needed to show a fatality rate below a human benchmark?
import math
human_rate = 1.25e-8          # fatalities per vehicle mile (about 1.25 per 100 million, illustrative)
for confidence in (0.80, 0.95, 0.99):
    miles = -math.log(1 - confidence) / human_rate      # zero fatalities observed (Poisson)
    print(f"{confidence:.0%} confidence, zero fatalities: {miles / 1e6:,.0f} million miles")
# with some fatalities observed, use the chi-square upper bound
def upper_rate(k, miles, conf=0.95):
    # exact Poisson upper bound by bisection
    lo, hi = 0.0, 50.0 + 10 * k
    target = 1 - conf
    for _ in range(100):
        mid = (lo + hi) / 2
        cdf = sum(math.exp(-mid) * mid ** i / math.factorial(i) for i in range(k + 1))
        lo, hi = (mid, hi) if cdf > target else (lo, mid)
    return hi / miles
for k, m in ((1, 300e6), (3, 500e6)):
    print(f"{k} fatalities in {m / 1e6:.0f} M miles: 95% upper bound = {upper_rate(k, m) * 1e8:.2f} per 100 M miles")

80% confidence, zero fatalities: 129 million miles
95% confidence, zero fatalities: 240 million miles
99% confidence, zero fatalities: 368 million miles
1 fatalities in 300 M miles: 95% upper bound = 1.58 per 100 M miles
3 fatalities in 500 M miles: 95% upper bound = 1.55 per 100 M miles

The calculation, similar to a widely cited 2016 RAND Corporation analysis, shows that hundreds of millions of miles without a fatality are needed to show statistically that an automated fleet is safer than human drivers, and that even a few fatalities widen the uncertainty considerably. This is why regulators and developers rely on safety cases combining simulation, closed-course testing, scenario-based assessment, analysis of disengagements and crashes, and safety management systems rather than mileage alone. Lesson 12 develops the safety case idea. UL 4600, a standard for the safety evaluation of autonomous products, sets out what such a safety case should contain.

Drones and other regulated robots

Drones are aircraft and are regulated by aviation authorities. In Canada, Part IX of the Canadian Aviation Regulations governs remotely piloted aircraft systems, with pilot certificates, registration, operating categories and rules on airspace and distances from people; amendments taking effect in November 2025 expanded the routes to lower-risk operations beyond visual line of sight. In the United States, the FAA's 14 CFR Part 107 governs small unmanned aircraft, with waivers for operations beyond visual line of sight, and a new rule for routine beyond-visual-line-of-sight operations was proposed in 2025. PHOT-350 and CON-250 cover drone operations in more detail. Other robots in regulated sectors include robots in nuclear facilities, regulated by the Canadian Nuclear Safety Commission or the US Nuclear Regulatory Commission; mining robots, under provincial mining regulations or the Mine Safety and Health Administration; and agricultural robots, which fall under farm safety rules and, for pesticide-spraying robots, pesticide regulation.