Tools: The 5 Levels of Humanoid Autonomy

The Framework: Agency vs. Dexterity ## Level 0: Scripted Motion (The Industrial Past) ## 5 Use Cases: ## Level 1: Intelligent Pick & Place (The Visual Awakening) ## 5 Use Cases: ## Level 2: Autonomous Mobility (The Explorer) ## 5 Use Cases: ## Level 3: Low-Skill Mobile Manipulation (The Founder's Sweet Spot) ## 5 Use Cases: ## Level 4: Force-Dependent Dexterity (The "Rodney Brooks" Wall) ## 5 Use Cases: ## Level 5: Fully General Autonomy ## The "ADAS vs. FSD" Split: Why One Size Won't Fit All ## Category 1: The "ADAS" Class (High Utility, Low Risk) ## Category 2: The "FSD" Class (High Agency, High Cost) ## What’s Your Bet? ## References If you scroll through X (Twitter) today, you’d think General Purpose Humanoids (GPH) are months away from folding our laundry and cooking 5-course meals. The reality is more nuanced and, for developers and founders, much more interesting. I’ve been digging into the "Self-Driving Levels" equivalent for robotics. We need a mental model to separate the hype (Level 5 sci-fi) from the commercial opportunities available right now. Based on frameworks from SemiAnalysis, insights from roboticist Rodney Brooks here is the definitive ladder of Humanoid Autonomy. Unlike self-driving cars, which just need to move safely, humanoids must move (Agency) and manipulate (Dexterity). Current commercial viability lies in balancing these two. Status: Mature (1980s–Present) These are the blind giants. They execute pre-programmed trajectories with sub-millimeter precision but have zero understanding of their environment. If you move the part by 1cm, the robot fails. Timeline: Mature. Famous Bots: FANUC M-2000, KUKA quantec. Status: Commercial Scale (2023–Present) Robots gained eyes. Using computer vision and deep learning, these systems can identify objects in a cluttered bin and pick them up. They don't "understand" the object's function, but they know where it is. Timeline: Standard in logistics by 2026. Famous Bots: RightHand Robotics, Covariant (software), Fanuc with iRVision. Status: Early Production (2024–2026) Robots gained Agency. They can map a new environment, navigate around obstacles, and decide how to get from A to B. This is where Boston Dynamics’ Spot shines. Note: They can move, but they can't do much with their hands yet. Timeline: Commercially viable now for inspection; scaling fast. Famous Bots: Boston Dynamics Spot, ANYbotics ANYmal. Status: Pilots -> Scale (2026–2029) This is the biggest opportunity for startups right now. These robots combine Level 2 mobility with Level 1 vision to perform loose manipulation tasks. They can pick up a box, move it across a room, and put it down. Crucial Insight: They struggle with force control. They can't thread a needle or peel a potato perfectly because they lack tactile feeling. But they can fry a basket of fries. Timeline: Pilots 2025; Scale 2027-2028. Famous Bots: Figure 01 (BMW pilot), Tesla Optimus (Factory transport), Chef Robotics (Modular arms). Note: You don't need legs for this! A wheeled robot with an arm is 80% cheaper and 100% more stable for a kitchen. Status: Research Lab (2028+) This is the barrier. To be a "General Purpose" humanoid, a robot needs tactile sensing (touch). It needs to feel if a screw is cross-threaded, or if a tomato is too soft to slice. Rodney Brooks (founder of iRobot) argues this is the "hard part" the industry is underestimating. We have great vision (VLAs), but terrible touch. Timeline: Research prototypes 2029; Commercial 2032+. Famous Bots: None commercially yet. Lab prototypes from MIT/Stanford. Status: Sci-Fi (2032?) A robot that can walk into a strange house, look around, and cook a specific family recipe using tools it has never seen before, without internet access. We often talk about humanoids as a monolith—one robot to rule them all. But look at the automotive industry. We didn't jump straight to Level 5 Robotaxis. Instead, we have a split market: 99% of cars have ADAS (Lane Keep, Cruise Control) and <1% attempt FSD (Full Self-Driving). Robotics will follow this exact same bifurcation. We aren't going to see a single "iPhone of Robots." Instead, Economics, Battery Life, Safety, and Compute will force the market into two distinct categories: The robotics industry is currently split between two philosophies: the "iPhone moment" where one hardware platform does everything (Level 4/5 Humanoids), and the "App Store" reality where specialized tools solve specific problems today (Level 3 Mobile Manipulators). I’d love to hear your take: Drop your predictions in the comments below! Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse - Agency: Perception, planning, and navigation in unstructured environments. - Dexterity: Grasping, force control, and fine manipulation. - Automotive Welding: The backbone of Tesla/Toyota factories. - Painting: Uniform spraying of car bodies. - Heavy Palletizing: Moving heavy boxes in completely caged, fixed zones. - PCB Assembly: Pick-and-place machines (high speed, zero intelligence). - CNC Tending: Loading raw metal into machines (requires precise fixturing). - Parcel Sorting: Identifying and grabbing random Amazon packages. - Agricultural Sorting: Picking good apples vs. bad apples on a conveyor. - Debris Recycling: Sorting plastic from glass in waste plants. - Kit Assembly: Grabbing 3 different items to put in a subscription box. - Quality Control: Visually inspecting parts and removing defects. - Industrial Inspection: Reading analog gauges in oil refineries. - Construction Patrol: Scanning progress on building sites (BIM verification). - Security: Autonomous patrolling of data centers or malls. - Hazard Mapping: Entering gas-leak zones to measure toxicity. - Last-Mile Delivery: Sidewalk robots (Starship) navigating crowds. - Specialized Cooking (The "Fry Cook"): Dumping baskets of fries, flipping burgers (requires timing, not fine touch). - Warehouse Restocking: Taking a tote from a pallet and sliding it onto a shelf. - Laundry Loading: Picking up dirty clothes and shoving them into a washer. - Hospital Logistics: Delivering lab samples or food trays to nurse stations. - Trash Collection: Navigating an office to empty bins into a main cart. - Full-Service Chef: Slicing veggies, seasoning to taste, plating delicate herbs. - Elder Care: Helping someone stand up (requires sensing their balance/frailty). - Skilled Trades: Installing electrical outlets or plumbing fixtures. - Textile Work: Buttoning a shirt or tying shoelaces. - Complex Assembly: Inserting flexible rubber gaskets into car doors. - The Build: Wheeled bases, specialized grippers, constrained compute (e.g., Jetson Orin Nano). - Battery & Economics: Wheels are 10x more energy-efficient than legs. Without the need to run a massive VLA model for every movement, these bots can run for 8-10 hours on a charge and cost <$10k. - Adoption Vector: These will dominate critical safety areas first. Think radioactive waste handling, chemical spill cleanup, or repetitive high-heat industrial cooking. The ROI is immediate because the task is defined. - The Build: Bipedal, humanoid hands, massive onboard inference compute. - Battery & Economics: Balancing on two legs consumes massive power. Running a "Common Sense" brain drains the rest. These will cost $50k+ and last 2-4 hours. - Adoption Vector: Research labs, luxury home help (eventually), and unstructured environments where wheels physically cannot go. - Do you think I’m underestimating how fast VLA (Vision-Language-Action) models will solve the "dexterity gap"? - Are you currently working on a Level 2 or Level 3 project? - What’s the one "boring" chore you’d pay a Level 3 robot to do right now? - [1] McKinsey: Humanoid Robots Crossing the Chasm - [2] 36kr: Rodney Brooks Technical Critiques - [3] Rodney Brooks: Why Today's Humanoids Won't Learn Dexterity - [4] SemiAnalysis: Robotics Levels of Autonomy