Jonathan Zinger
Mind Map by , created over 5 years ago

Mind Map on Robotics, created by Jonathan Zinger on 05/08/2014.

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Jonathan Zinger
Created by Jonathan Zinger over 5 years ago
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1 Agents
1.1 Autonomous Robots
1.1.1 Architecture
1.1.1.1 Rebellion
1.1.1.1.1 Brittle
1.1.1.1.1.1 Computationally Expensive
1.1.1.1.1.1.1 Slow (NP-Hard or worse)
1.1.1.1.2 Subsumption - Brooks
1.1.1.1.2.1 Stateless Behavior-Based Architectures
1.1.1.1.2.1.1 Agent Ignores sensor, does hard-coded thing "always go forward"
1.1.1.1.2.1.2 Act based on sensor, no memory
1.1.1.1.2.1.3 Arbitration
1.1.1.1.2.1.3.1 Voting
1.1.1.1.2.1.3.2 Simultaneous
1.1.1.1.2.1.3.3 Precedence
1.1.1.1.2.1.3.4 Subsumption
1.1.1.1.2.2 Stateful Behavior Based Architectures
1.1.1.1.2.2.1 Need memory if environment doesn't include all clues needed to make decisions
1.1.1.1.2.3 Subsumption Architecture
1.1.1.1.2.3.1 Parallel
1.1.1.1.2.3.2 Arbitration
1.1.1.1.2.3.3 Message Passing
1.1.1.1.2.3.4 Inhibit
1.1.1.1.2.4 Hybrid - hierarchical with subsumption behaviors
1.1.1.2 3 tiered
1.1.1.2.1 The Wrangler
1.1.1.2.1.1 Deliberator
1.1.1.2.1.1.1 Executive
1.1.1.2.1.1.1.1 Control
1.1.1.2.1.1.1.1.1 Effectors
1.1.1.2.1.1.1.1.1.1 World
1.1.1.2.1.1.1.1.1.1.1 Sensors
1.1.1.2.1.1.1.1.1.1.1.1 Feature Selection
1.1.2 Agent with real world environment
1.2 Continuous Behavior
1.3 FSA Macros
1.4 Motor Schema Behaviors
1.5 Multiagent Systems
1.5.1 Cooperative
1.5.2 Competitive
1.5.3 Multiagent Learning
1.5.3.1 Team Learning
1.5.3.1.1 Learning a solution for multiple agents
1.5.3.2 Collaborative Learning
1.5.3.2.1 Multiple agents learning solutions
1.6 Self Contained (no joystick)
1.7 Environmental Feedback
2 Bayes Filters
2.1 Kalman
2.1.1 Gaussian distribution defines where robot is located
2.2 Particle
2.2.1 Distribution is a random sample of points in your space. Use EC like fitness-based selection to choose parents for next generation of points
2.3 Tell where the robot is probably located
2.4 Prior Prob of Robots State
2.5 Transition Model
2.6 Sensor Model

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