Lectures

All lecture recordings.

Module 0: Imagine Day

L00 Tue 07 Sep: No class. Skim the syllabus. Come to next class with a sketchbook!

Module 1: Human and Robot Bodies


Sensation: How do robots and humans sense the world?

Read this before class

L01 Thu 09 Sep: Syllabus, class website and Intro to Arduino. Notes: L01 – Sensation I.
L02 Tue 14 Sep Living Things Are Not (20th Century) Machines. Notes: L02 – Sensation II. Recording.

Links to components and/or related materials:

Photo resistor
Ultrasonic Sensor
Analog to Digital Converter

Learning Goals

Knowledge: Describe (in words or pictures) a sensation circuit and Arduino control loop
Problem Solving: Design (on paper) a circuit that reacts to a sensation
Creativity: Analyze (in words or pictures) or design a real life object’s sensation circuit
Critique: Compare (in words) robot sensation to human sensation


Actuation: How do robots and humans move their bodies?

L03 Thu 16 Sep: Neurons, Synapses, Action Potentials, and Neurotransmission. Notes: L03 – Actuation I. Recording.
L04 Tue 21 Sep: The Proprioceptive Senses. L04- Actuation II. Recording.

Links to components and/or related materials:

Mechanical animations
A Cool Pick and Place Robot?
Different Kinds of Pick and Place Robots 
Encoders

Learning Goals

Knowledge: Describe a motor control circuit
Problem Solving: Design an actuator that can reach a position
Creativity: Analyze or design a real-life object’s actuator mechanism
Critique: Compare robot actuators to your own body’s actuation


Control: How do you communicate between parts of a robot or human body?

L05 Thu 23 Sep: Robots: Digital & Analog. Notes: L05 – Control I. Recording.
L06 Tue 28 Sep:
How Does a PID Controller Work?
PID Demo Video
PID Simulator Online
Notes: L06 – Control II. Recording.

Note: you may want to look through next week’s synchronization links  for this lecture.

Learning Goals

Knowledge: Describe how gradual error correction works for humans and robots
Problem Solving: Apply the process of gradual error correction to a simple robot task
Creativity: Analyze or design a real-life error correction function
Critique: Compare neuronal control to robotic control


Synchronization: How can we synchronize components of a body or system?

L07 Thu 30 Sep: Class cancelled. Supplementary notes here.

L08 Tue 05 Oct: Notes: L07 – Synchronization. Recording.

Synchronicity (Thailand)
Synchronization of Metronomes (entrainment)
Synchronized Flashing among Fireflies (optional but recommended)
Neurobiological foundations of neurologic music therapy

Learning Goals

Knowledge: Describe the fundamental problems of synchronization
Problem Solving: Implement the synchronization protocol for real or electronic fireflies
Creativity: Analyze or design a real-life synchronization protocol
Critique: Identify intelligent behaviours that seem to “just” be synchronization


Module 2: Emergent Behaviour


Automata: How can complex behaviours emerge from simple rules?

L09 Thu 07 Oct:
Notes: L08 – Automata. Recording.
Conway’s Game of Life Online
Langton’s Ant Online
Cellular Automaton Explanation (optional)

L10 Tue 12 Oct:

Notes: L09 – Automata II. Recording.
Automaton Simulator Online
Embodied cognition is not what you think it is

Learning Goals

Knowledge: Describe the “rules” of cellular and finite state automata
Problem Solving: Design an automaton that finds something
Creativity: Design an automaton that works with different media, dimensions, etc.
Critique: Compare the emergence we see in automata to biology


Swarms: How can automata work together to make decisions emerge?

L11 Thu 14 Oct:
Notes: L10 – Swarms I. Recording.
Swarm Robots Video
Flocking Online (optional)
A Brainless Slime That Shares Memories by Fusing (optional)
Physarum (optional)
Slime Mold Simulator Online (optional)

L12 Tue 19 Oct:
Notes: L11 – Swarms II. Recording.
Swarm Robotic Behaviors and Current Applications

Knowledge: Describe a computational model of swarm behaviour
Problem Solving: Design a swarm behaviour that “finds” something
Creativity: Analyze or design a real-life swarm behaviour
Critique: Compare swarms intelligence to human intelligence


Utility: How do we guide swarm units in adapting their decision strategies?

L12 Thu 21 Oct:
Notes: L12 – Utility I. Recording.

Weighted Bees Example
Rock, Paper, Scissors
Game Theory and Robotics

L13 Tue 26 Oct: Utility Theory Introduction

KnowledgeDescribe how a utility function works to make a swarm “learn”
Problem SolvingDesign a utility function that “learns” a strategy
CreativityAnalyze or design a real-life utility function
Critique: Compare learning with a utility function to human learning


Distribution: What’s the difference between distributed and “unified” systems?

L14 Thu 28 Oct:
The Distributed Mind: Octopus Neurology
Nature’s internet: how trees talk to each other in a healthy forest
Optional scientific reading for above video

L15 Tue 02 Nov:
On Having No Head: Cognition throughout Biological Systems
On Body Memory and Embodied Therapy (optional)

Knowledge: Describe the fundamental problems of distribution
Problem SolvingApply message-passing protocols a simple robot task
CreativityAnalyze or design a real-life distributed system
Critique: Compare distributed intelligence to unified intelligence