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Human vs automatic design in swarm robotics
Human vs Automatic-design:
AutoMoDe
Edgar Buchanan
edgar.buchanan@york.ac.uk
Department of Electronic Engineering
Previous Work AutoMoDe
Human vs
Automatic Design
Previous Work
Bottom-up approach
Task
Robot Robot Robot
Top-down approach
Task
Robot Robot Robot
Design methodology
Mathematical
model
Simulation Hardware
Hand designed controllers
Hand designed controllers
•Advantages
•See progress (Visual inspection)
•Clear understanding of the controller
•Downside
•Takes a long time (trial-and-error)
•Bias introduction
Automated controller design
Automated controller design
•Advantages
•Takes less time
•No bias introduction
•Disadvantage
•Complex controller
•Reality gap
AutoMoDe
What is a state
machine?
Human vs automatic design in swarm robotics
State 1
Modules
State 2
State 3
State 4
State 5
State 6
Actions
Action 1
Action 2
Action 3
Action 4
Action 5
Action 6
Action 7
Action 8
Action 9
Finite State Machine
State 1 State 3
State 4 State 6
Action 5
Action 6
Action 8Action 9 Action 7
Manual design
Human vs automatic design in swarm robotics
Human vs automatic design in swarm robotics
Exploration
Modules
Stop
Phototaxis
Anti-
phototaxis
Attraction Repulsion
Actions
Black-floor
White-floor
Inverted-
Neighbour-count
Gray-floor
Neighbour-count
Fixed-probability
How?
AutoMoDe
(Automatic Modular Design)
State 1 State 3
State 6
Action 5
Action 8Action 7
AutoMoDe
(Automatic Modular Design)
State 1
State 4 State 6
Action 6
Action 9 Action 7
AutoMoDe
(Automatic Modular Design)
State 1 State 3
State 4
Action 5
Action 9 Action 7
AutoMoDe
(Automatic Modular Design)
State 3
State 4 State 6
Action 6
Action 8
Action 7
State 1 State 3
State 6
Action 5
Action 8Action 7
State 1
State 4 State 6
Action 6
Action 9 Action 7
State 1 State 3
State 4
Action 5
Action 9 Action 7
State 3
State 4 State 6
Action 6
Action 8
Action 7
0.1 0.5
0.4 0.8
AutoMoDe (Automatic Modular Design)
•Controllers made with pre-defined modules and
conditions.
•Human readable controllers
•An optimizator generates the best controller
•Works for any robot (a hardware interface is needed)
AutoMoDe
solution:
Attraction Stop
(β=1.0)
Black-floor
Gray-floor (β=1.0)
Fixed-probability (β=0.25)
Human vs Automatic design
VS
•Methods:
•Unconstrained human (U-Human)
•Constrained human (C-Human)
•Neural network (EvoStick)
•AutoMoDe with F-Race (Vainilla)
•AutoMode with Iterative F-Race (Chocolate)
Unconstrained human (U-Human)
Constrained human (C-Human)
Neural network (EvoStick)
Neural network (EvoStick)
Which one is
the best?
Human vs automatic design in swarm robotics
Human vs automatic design in swarm robotics
Human vs automatic design in swarm robotics
Human vs automatic design in swarm robotics
Reading
[1] AutoMoDe: A novel approach to the automatic
design of control software for robot swarms. [Article]
[2] An experiment in automatic design of robot
swarms. [Article]
[3] AutoMoDe-Chocolate: Automatic design of control
software for robot swarms. [Article]
[4] Automatic design of robot swarms: achievements
and challenges. [Article]

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Human vs automatic design in swarm robotics