Robot Holidays: Real AI Automation Wins in 2025

A single factory automation tweak helped a 150-year-old American lock maker jump from 1,500–1,800 finished locks per shift to more than 5,000. That’s not a “future of work” slideshow. That’s Tuesday.

This week’s robotics round-up (shared in IEEE Spectrum’s Video Friday series) looks festive on the surface—holiday greetings from labs and robot companies around the world. But under the tinsel is a pretty clear signal for anyone building products, running operations, or funding R&D: AI-powered robotics is becoming practical in more places, with better economics, and with clearer pathways to deployment.

As part of our “Artificial Intelligence & Robotics: Transforming Industries Worldwide” series, I’m going to treat these videos like field notes. What do they tell us about where robotics is working right now (late 2025), what’s still hard, and how teams can make smarter decisions in 2026?

The real story behind the “holiday robot videos”

Answer first: The holiday montage is fun, but the meaningful pattern is that robotics progress is now driven by deployment constraints—safety, reliability, maintainability, and unit economics—not just cool demos.

Holiday greetings from groups like FZI, Norlab, Fraunhofer IOSB, HEBI Robotics, Toyota Research Institute, Clearpath, Robotnik, and ABB Robotics are a reminder that the robotics ecosystem has matured into a global supply chain of ideas and components. That matters because robotics rarely succeeds as a solo act. Most production robots are a stack:

• A hardware platform (arm, base, gripper, sensors)
• Controls and safety systems
• Perception (often deep learning)
• Task and motion planning
• Workflow integration (MES/ERP/WMS, QA, logging)
• Serviceability (spares, uptime, remote support)

The labs and companies posting “Happy Holidays” are also the ones shipping parts of that stack. If you’re a business buyer, this is your cue to stop thinking “Which robot should we buy?” and start thinking “Which stack do we trust to operate at 95%+ uptime in our environment?”

Manufacturing automation: the KPI that makes executives pay attention

Answer first: Industrial robotics is still the highest-confidence ROI area, and the best wins come from pairing mature robot arms with very smart tooling and workflow design.

The most concrete business result in the feed comes from a FANUC-based system built for Wilson Bohannan, a lock maker that stayed in the U.S. for more than 150 years. The system uses two high-speed, high-precision FANUC M-10 series robots and end-of-arm tooling designed to handle 18 padlock styles. The outcome is bluntly measurable: from 1,500–1,800 locks per eight-hour shift to more than 5,000.

Here’s what I like about that example: it’s not “AI magic.” It’s an engineering truth executives can budget for.

What actually drove the throughput jump

In most factories, robot arm selection gets too much attention. The real determinant of throughput is often:

1. Fixturing and end-of-arm tooling (EOAT): If EOAT can reliably accommodate product variation, the cell stops being brittle.
2. Changeover strategy: Supporting 18 styles without painful changeovers means less downtime and fewer operator errors.
3. Cycle time stability: You don’t win by hitting a peak speed once; you win by holding stable speed for months.

If you’re planning an automation project for 2026, take a stance: fund the tooling engineering as aggressively as the robot purchase. The robot is the visible part; tooling is where many projects either become robust or die quietly.

A practical checklist for buyers

If you’re evaluating industrial automation (robot arms, cobots, or mobile manipulators), ask vendors or integrators:

• What’s the measured OEE impact expected in the first 90 days?
• What failure modes will stop the line (mis-picks, jams, part variation)?
• What’s the mean time to recovery when something goes wrong?
• Who owns cell tuning after deployment—your team or theirs?

The goal is to shift the conversation from “capabilities” to operational proof.

Robot dogs for wildfire protection: where embodied AI earns its keep

Answer first: Environmental monitoring is becoming a mainstream robotics use case because it combines high-value sensing with tasks too risky or too repetitive for people.

DEEP Robotics deployed China’s first robot dog patrol team for forest fire protection in the West Lake area. This isn’t about novelty. Fire prevention is a brutal operations problem:

• You need frequent patrol coverage.
• Conditions change quickly (wind, heat, human activity).
• Early detection is everything.

Quadruped robots fit because they handle uneven terrain better than many wheeled systems. Add embodied AI—perception models, anomaly detection, terrain-aware navigation—and you get a platform that can patrol, scan, and report without exhausting human teams.

Where this is headed in 2026

Expect “robot dogs for safety” to expand beyond forests:

• Utilities: substation and transmission corridor inspections
• Oil & gas: perimeter monitoring and leak/thermal anomaly detection
• Mining and tunneling: patrol plus gas/air quality sensing
• Municipalities: inspection in parks, flood-prone zones, and remote assets

The business case is usually a mix of:

• Lower incident probability (fires, outages)
• Faster detection and response
• Better data trails (auditability for compliance)

One caution: the robot is only half the system. The other half is an alert pipeline that routes credible events to humans without drowning them in false positives.

Modular robots and humanoids: flexibility is the product

Answer first: Modular configurations and humanoid platforms are chasing a specific prize—robots that can be repurposed across tasks without a full re-engineering cycle.

LimX Dynamics shows TRON 2, a modular robot that can be configured as dual-arm, bipedal, or wheeled depending on the mission. This is a strong indicator of what robotics buyers actually want: a platform that survives changing requirements.

Manufacturing, logistics, and field operations rarely stay stable. SKUs change. Facilities get rearranged. Compliance rules evolve. Modular robots aim to reduce the “rebuild tax” every time reality shifts.

The humanoid “app store” debate (and why it’s harder than it sounds)

Unitree’s mention of a humanoid “app store” is provocative, and I’m skeptical for one specific reason: a robot app store can’t thrive without a platform people buy for its core function first.

Phones succeeded because the core utility (communication, camera, internet) was already compelling. For humanoids, the equivalent would be something like:

• Reliable package handling in mixed environments
• Safe, consistent material movement
• Night-shift “boring work” coverage with minimal supervision

Until humanoids can do one or two of those at predictable cost, an app ecosystem will feel premature.

That doesn’t mean software marketplaces won’t happen. They will. But in robotics, marketplaces tend to cluster around integrations and validated behaviors (calibrated perception models, certified safety behaviors, and deployment-tested task templates), not “download an app and it just works.”

Soft goods manipulation: towel folding is the quiet benchmark

Answer first: Deformable object handling (laundry, linens, bags) is still one of the hardest problems in robotics, and every towel-folding demo is a serious signal.

Kinisi Robotics shows an end-to-end system that folds a towel autonomously—a task that looks trivial until you try to do it with a machine. Cloth changes shape continuously, self-occludes, wrinkles, and behaves differently based on humidity and fabric type.

This is why towel folding matters beyond laundry. It’s a proxy for a whole class of industrial tasks:

• Packaging flexible materials (pouches, mailers)
• Food handling (irregular shapes)
• Medical textiles and sterile processing
• E-commerce returns (bags, garments)

What successful deformable manipulation stacks share

Teams that make progress here typically combine:

• Perception that can infer key points and edges despite occlusion
• Closed-loop control (the robot adjusts mid-action, not after failure)
• Tactile or force feedback (or very smart vision substitutes)
• Training data that reflects real variability, not perfect lab setups

If you’re considering automation in apparel, healthcare linen, or packaging, don’t accept a single perfect demo as proof. Ask for:

• Performance across multiple fabric types
• Misfold rates and recovery behavior
• Maintenance needs (gripper wear, camera recalibration)

Robotics in harsh environments: move the electronics out of harm’s way

Answer first: Remote actuation and electronics separation is a practical design pattern for robots that must operate in heat, dust, radiation, underwater, or high EMI.

JSK Lab’s REWW-ARM is a remote wire-driven mobile robot designed to keep electronics off the mobile part, enabling operation in harsh environments on land and underwater. This is the kind of unglamorous engineering that expands where robots can go.

Why it matters for industry:

• In nuclear decommissioning or disaster response, electronics are a liability.
• In underwater work, sealing and pressure management drive cost.
• In high-temperature zones, sensors and compute degrade fast.

Designing around these constraints can be cheaper than over-hardening electronics. It’s also more maintainable—swap modules, keep compute in a safe zone, service the “hot” end as a consumable.

Mars rover records: autonomy is a logistics strategy

Answer first: NASA’s Perseverance driving a record distance shows why autonomy is valuable even when labor isn’t expensive—because the “labor” is separated by time and physics.

NASA shared Perseverance’s POV from a record-breaking drive on June 19, 2025 (Sol 1540): 1,350.7 feet (411.7 meters) in 4 hours and 24 minutes, beating the prior record of 1,140.7 feet (347.7 meters) set on April 3, 2023.

That’s not just a fun stat. It highlights a theme businesses often miss: autonomy is a throughput tool when remote operation is slow, expensive, or delayed.

On Earth, the same logic shows up in:

• Remote inspection of wind farms and offshore assets
• Warehouses running overnight with minimal staffing
• Mining sites where operators may be kilometers away

Autonomy isn’t about removing humans. It’s about using human judgment where it’s scarce and letting robots handle the “keep moving” layer.

Events and what to watch next: ICRA 2026 and the commercialization gap

Answer first: The next wave of robotics winners will be the teams that close the gap between research demos and dependable operations.

The calendar callout for ICRA 2026 (1–5 June 2026, Vienna) matters because ICRA is where you can often spot the next two years of robotics priorities: dexterous manipulation, generalist policies, safety proofs, sim-to-real reliability, and compute-efficient models.

Here’s my bet for what will separate strong robotics programs in 2026:

• Validation in messy environments: Not a lab bench. Real floors, real lighting, real downtime constraints.
• Service model maturity: Spare parts, remote diagnostics, clear SLAs.
• Integration readiness: Robots that fit into existing workflows (barcode systems, QA, audit logs).

A robotics demo becomes a product when “what happens on a bad day” is engineered, documented, and supportable.

What business leaders should do next (without overbuying hype)

Answer first: Start with a narrow, high-frequency task; demand uptime metrics; invest in tooling and integration; and treat AI as a reliability layer, not a magic wand.

If you’re planning robotics adoption in 2026—manufacturing, inspection, logistics, or environmental monitoring—use this short action plan:

1. Pick one workflow with painful repetition. If it happens 1,000 times a day, it’s a good candidate.
2. Define success in numbers. Throughput, scrap rate, incident rate, mean time to recovery.
3. Budget for integration. The robot is rarely the expensive part once you count engineering time.
4. Pilot in production conditions. Variable lighting, dirty floors, shift changes, operator handoffs.
5. Plan support on day one. Training, spare parts, remote monitoring, escalation paths.

Holiday videos are a nice reminder that robotics is built by people—and that the field has a culture of sharing progress. But the bigger lesson is more practical: AI and robotics are already transforming industries worldwide, and the winners are the ones treating deployment like the main product.

If you’re thinking about where to place your next bet—robot dogs for safety, modular platforms for flexible automation, or industrial arms for throughput—ask a simple question: Which of these systems can you keep running when your best operator is off-shift and the environment isn’t cooperating?