Skip to content
The End Effector
Sign inJoin

Plot Your Robot on the Map

The commercial robotics map has six crowded zones and vast empty ones. Plot a robot on the grid and find its category.

EarthwardAtomsBitsApril 19, 2026
SYSTEM MAP

Find your robot

Sensing-limited
2Sensing2Perception2Planning2Control2Actuation2Environmentsystem avg2.0

Teardown: System Map

Bottleneck Identification

bottleneck = min(applicable_ratings) = Sensing (rating 2/3)

bottleneck_count = 6 subsystems at minimum rating

The chain performs at the level of its weakest link. All other subsystems are constrained by this bottleneck.

System Health

avg_rating = sum(applicable) / count = 2.00

applicable_count = 6 (subsystems with rating > 0)

Rating Vector

ratings = { SENS: 2, PERC: 2, PLAN: 2, CTRL: 2, ACT: 2, ENV: 2 }

node_radii = [ 30px, 30px, 30px, 30px, 30px, 30px ]

chain = SENS → PERC → PLAN → CTRL → ACT → ENV → (feedback to SENS)

Assumptions

medium impact

The two-axis model (autonomy x mobility) captures the primary strategic dimensions but omits others (payload, precision, environment harshness) that matter for specific applications.

low impact

Manipulation capability is treated as a modifier rather than a primary axis. A full three-axis model would be more accurate but harder to visualize on a 2D map.

Sources

International Federation of Robotics (2025). World Robotics 2025: Industrial Robots.

Amazon (2025). Corporate filings — robotics fleet data.

Module 01: What Robots Actually Are — taxonomy table and category definitions.

Rate each subsystem (0-3)

SENS
PERC
PLAN
CTRL
ACT
ENV

Similar bottleneck pattern

Agricultural Drone (DJI Agras)

GPS + limited onboard sensing constrains autonomy. Better sensors = better coverage planning.

Industrial Arm (FANUC, KUKA)

Mature control and actuation, but limited sensing keeps them caged. Better sensing enables human coexistence.

Teardown: Bottleneck Pattern Matching

Pattern Match

bottleneck_id = sensing

matching_examples = EXAMPLE_ROBOTS.filter(r →r.bottleneck === "sensing")

matches = 2 robots (Agricultural Drone (DJI Agras), Industrial Arm (FANUC, KUKA))

Real-world robots are matched by identifying which subsystem is their primary operational constraint.

Visual Encoding

node_radius = 18 + rating * 6 px

connection_width = 1 + min(rA, rB) * 1.5 px

connection_color = RATING_COLORS[min(rA, rB)]

Weakest-link principle: each connection is constrained by its lowest-rated endpoint.

Assumptions

medium impact

Category centers are positioned using consensus industry positioning as of early 2026. These positions shift as technology matures.

medium impact

Euclidean distance on a 1-5 scale treats autonomy and mobility as equally weighted. In practice, the difficulty of advancing along each axis is nonlinear.

low impact

Six reference categories represent the major commercial segments. Niche categories (underwater ROVs, space rovers) are not modeled.

Sources

IFR World Robotics 2025 — Market segmentation for industrial arms, cobots, AMRs.

Module 01 taxonomy table: autonomy and mobility classifications with example companies.

Figure AI press release (September 2025) — $39B valuation, Series C.

▸ THE DEBRIEF

Your system is sensing-limited (rated 2/3). The sensing subsystem constrains overall system performance. Agricultural Drone (DJI Agras) shares this bottleneck pattern.

What to take away

  • 01Six categories dominate commercial robotics; every viable product maps to one of them on the autonomy-mobility grid. Most of the remaining grid coordinates stay empty because unit economics collapse before any design reaches production scale.
  • 02Humanoid platforms are racing to occupy the one quadrant no commercial robot has solved: dexterous manipulation paired with free-roaming mobility. Boston Dynamics Atlas, Figure 01, and Agility Robotics Digit each target this space, yet none has cleared unstructured real-world deployment at scale.
  • 03Industrial arms have occupied the fixed, low-autonomy zone for four decades and still represent a $16.7 billion annual market; new categories open new zones rather than displacing old ones.
  • 04A robot's position on the autonomy-mobility grid locks its MACRS depreciation (5-year for fixed manipulators, 7-year for mobile platforms), regulatory regime (FAA or OSHA), and cost of capital before engineering begins.

Six categories account for almost every robot a reader is likely to encounter: industrial arms, collaborative robots (cobots), surgical systems, warehouse autonomous mobile robots (AMRs), delivery drones, and humanoids. Each occupies a narrow zone on a two-axis map of autonomy and mobility. Between those zones sit large regions of empty space. Those regions are empty because nothing has yet cleared the combined engineering, cost, and regulatory gates required to commercialize them.

Three axes define every robot's position in this map: autonomy (teleoperated to fully self-directed), mobility (bolted down to legged and free-ranging), and manipulation (none through dexterous). Your answers place a dot on the map. A text callout identifies the nearest established category, reports whether the robot sits inside that category's proven zone or adjacent to it, and flags the single most dangerous combination: dexterous manipulation paired with free-roaming mobility. That combination is the territory Boston Dynamics, Figure, and 1X are each spending billions attempting to claim.

The six category centers are drawn from the International Federation of Robotics' 2025 World Robotics report, Amazon's disclosed 750,000-unit robot fleet as of 2025, Figure AI's September 2025 Series C valuation, and Intuitive Surgical's deployed da Vinci fleet. Distances are Euclidean on a five-point scale. A robot within 1 unit of a category center is inside that category; 1 to 2 units away is adjacent to it; beyond 2 units sits in territory no commercial category has proven yet.

Start by placing a robot you know well: your Roomba, an Amazon warehouse shuttle, or a car-assembly line arm. Confirm the model agrees with your intuition, then drag a point into one of the empty quadrants. A mobile manipulator with dexterous hands and full legged locomotion is the moonshot every humanoid company is chasing, which is why development timelines run in years rather than months. This tool is diagnostic: it shows where a robot sits today, not whether the empty territory it targets is about to be colonized.

By Jonathan Miller/Revised May 11, 2026

tee-ix-int-01-02-20260419-8fde4e

Miller, J. (2026). Plot Your Robot on the Map [Interactive]. Interactives, The End Effector. https://endeff.com/ix/int-01-02 (tee-ix-int-01-02-20260419-8fde4e)

Referenced in

Revision history · 2
  1. Apr 24, 2026tee-ix-int-01-02-20260424-e3b05f

    Narrative lint — voice, specificity, structure.

  2. Apr 19, 2026tee-ix-int-01-02-20260419-8fde4e

    Initial editorial draft.

Originally published alongside Core Robotics

roboticstaxonomymarket-structure