Subsumption Architecture: Layered Reactive Robot Control

Behavior Layers (priority arbitration)

1 · Avoid Obstaclehighest

2 · Seek Lightmid

3 · Wanderdefault

Environment

Obstacle count 14

Robot speed 2.2 u/s

Avoid sensor range 2.6 u

Live Telemetry

Active layer

WANDER

Nearest obstacle

Dist to light

Lights reached

How it works

Rodney Brooks' subsumption architecture (1986) replaced the classical sense→model→plan→act pipeline with a stack of independent, concurrently-running reactive behavior modules, each wired directly from sensors to motors. No layer holds a world model; each only sees what it needs.

Higher layers subsume — inhibit and override the motor output of — lower layers when their own trigger condition is active. This robot runs three layers, evaluated top-down every frame:

for each frame:
  if minObstacleDist < avoidRange:      # Layer 1 — highest priority
      heading → away from obstacles
  elif seekEnabled:                     # Layer 2 — subsumed by 1
      heading → toward light target
  else:                                 # Layer 3 — default fallback
      heading → random walk

position += speed * dir(heading) * dt

The steering vectors themselves are simple potential fields: Avoid sums (robotPos − obstaclePos) / dist² over every obstacle inside sensor range, so closer obstacles push harder. Seek points straight at the glowing light target. Wander adds small random jitter to the current heading. No layer ever "asks permission" from another — arbitration is a fixed priority switch, which is why the panel above lights up exactly one active layer at a time.

Avoid ON/OFF — disable Layer 1 to watch the robot drive straight through obstacles.
Seek ON/OFF — disable Layer 2 to see pure wander-and-avoid with no goal.
Obstacle count / sensor range — denser arenas or a shorter sensor range make Avoid dominate more of the time; the telemetry panel shows this directly.

This is the same layered-priority idea used in real behavior-based robots — from Brooks' original six-legged walker Genghis to modern vacuum robots that flee a cliff sensor before anything else, however "smart" their higher-level path planning is.

Robot Light target Obstacle

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