Project topics in artificial intelligence and robotics
Embodied affective
Robotics
Robotics
Andrés Faiña, CS
anfv@itu.dk
Kasper Støy, CS
ksty@itu.dk
Mechatronics
Bioinspired and swarm robotics
Payam Zahadat, CS
paza@itu.dk
Machine
Learning
Lab Automation
Neural Networks
Sebastian Risi, DD
sebr@itu.dk
People
Nicolas Bessone,
CS nbes@itu.dk
Jonas H Jensen, CS
jhaj@itu.dk
Djordje Grbic, DD
djgr@itu.dk
Joachim Winther Pedersen, DD jwin@itu.dk
Elias Najarro, DD
enaj@itu.dk
Rodrigo Moreno Garcia, CS
rodr@itu.dk
Morten Roed
Frederiksen
mrof@itu.dk
Four thesis elements
Build robot Prototype
Simulation
Control software
Artificial intelligence
Application domain
Experiments
Existing
Robot
Research
topic
Overview of topics
Bio-inspired and swarm robotics
learn from nature’s amazing solutions
Take inspiration from natural systems
Design algorithms for robotic systems
Contact: Payam - paza@itu.dk
Evolutionary Robotics:
Evolving a General Communication Space for Robotic Swarms
a novel, general approach to evolve reliable and explainable communication in swarms of robots, and in particular the interplay between behavior and communication.
Contact: Payam - paza@itu.dk
Dynamic collectives: static formations consisting of internal dynamics
Contact: Payam - paza@itu.dk
Develop algorithms for swarms of autonomous robots.
The overall shape of the collective is static, but those who form it are dynamic (circulating within the swarm or constantly leaving and joining).
Maritime Robotics
Applying swarm and modular robotics to develop new approaches in container shipping.
Contact: Payam - paza@itu.dk
Robots vs Anxiety
Contact: Morten (mrof@itu.dk)
Can demands and caretaking needs spark a stronger affective connection with therapeutic robots?
This project will investigate if introducing tamagotchi-inspired demands to a pocked-sized therapeutic robot can catalyze stronger motivation to interact with the robot.
Contact: Morten (mrof@itu.dk)
Tactile robot communication
Modular robots
Contact: Andres Faina (anfv@itu.dk)
Office: 2F18
Robotic Modules
Modular robots built by assembling modules
Evolutionary modular robots
Contact: Andres Faina (anfv@itu.dk)
Evolving modular robots in GPU
Contact: Andres Faina (anfv@itu.dk) and Rodrigo Moreno (rodr@itu.dk )
https://vimeo.com/540894612
Optimizing modular robots in the real world with bayesian methods
Contact: Andres Faina (anfv@itu.dk) and Rodrigo Moreno (rodr@itu.dk )
https://vimeo.com/540894612
Robots that are able to grow
Contact: Andres Faina (anfv@itu.dk)
Active inspections in factories
Contact: Andres Faina (anfv@itu.dk)
Valve Identification and Grasping for a Quadruped Robot in an Industrial Setting
Design and Simulation of a Quadruped-Based Deployment Strategy for an Aerial Inspection Drone
UAV System for Active Inspection in the Pharmaceutical Industry
Automated design of machines
Contact: Andres Faina (anfv@itu.dk)
Educational electronic simulator
Contact: Andres Faina (anfv@itu.dk)
DO NOT TRY THIS CIRCUIT!
Evolved Soft Robots
A lot of soft robots have been evolved in simulation, but there is not a fast way to build them
Can we make modular soft robots to build the evolved robots?
Can we create robots that are able to grow?
Contact: Andres Faina (anfv@itu.dk)
Swarm robotics
Contact: Andres Faina (anfv@itu.dk)
Origami Robotics
Explore the creation of 3D printed origami mechanisms for use in soft robotics.��Design new origami mechanisms
Investigate print in place solutions for robotic end effectors
Contact: Bailey Dacre baid@itu.dk
Morphing buoyancy robot
Liquid
Contact: Rodrigo Moreno rodr@itu.dk
Applications:
Chemistry, measure features in liquids
Underwater monitors/cameras
How can a robot change its whole shape to change its buoyancy?
Vibration sensing for liquid level in vessels
Similar techniques for identifying solids and changes in solids
Contact: Rodrigo Moreno rodr@itu.dk
Smart, portable testing of water treatments with automatic modules
Contact: Rodrigo Moreno rodr@itu.dk
From robot to API in hardware
How to automate the generation of controller Arduino libraries from robot specifications:
Datasheet of the device + requirements ->Auto generated Arduino code -> Verification
Some past work in drivers for operating systems:
Contact: Rodrigo Moreno rodr@itu.dk
Chemistry with Modular Reconfigurable Lab Automation
Dive into control, simulation, mechatronics, and machine learning with our system.
—no chemistry background needed.
Large-scale co-evolution in a Massively Multi-agent Game environment
Contact: Sebastian Risi (sebr@itu.dk)
REPURPOSE Project: Repurposing Existing Video Games for Citizen Science
Contact: Sebastian Risi (sebr@itu.dk)
Optimal Number of Bio-Inspired Learning Rules for Adaptive Neural Networks
Extend algorithm for evolving plastic neural networks to find the optimal number of unique plasticity rules.
Plasticity rules make neural networks more adaptive.
Plasticity rules can be optimized to control multiple network connections.
Can we through evolution find
the perfect number of unique
plasticity rules that enables
optimal adaptiveness of
bio-inspired neural networks?
Research Question:
Contact: Joachim Winther Pedersen jwin@itu.dk
Evolving computational graph topologies
Exploring the how agent adaptation is facilitated by cognition encoded in graph structures
Contact: Djordje- djgr@itu.dk
How does sparsely connected neural-network allows agent to continually adapt to novel stimuli?
Gaining insights with Agent-based models (ABM)
Exploring the how multi-agent simulations can help us learn about collective outcomes
Contact: Djordje- djgr@itu.dk
Can reinforcement-learning-based improve ABMs?
Build products informed by emergent behavior in ABMs?
Make a GPU-accelerated Minecraft clone
Contact: Djordje- djgr@itu.dk
Language Cellular Automata
Combining Neural Cellular Automata models with Language models to get a language interface to cellular automata models
#NCA #LLMs #Generative
Contact: Elias Najarro, Eleni Nisioyi,
Milton Montero
enaj@itu.dk, enis@itu.dk, mlle@itu.dk
Climbing generator
Build a generative model for climbing routes & boulder problems using a combination of 3D pose estimation and reinforcement learning simulations
#RL #Generative models
Contact: Elias Najarro, Milton Montero
Open-endedness in Minecraft
Running evolutionary simulations with LLM agents in Minecraft survival mode to study the emergence of open-ended strategies
#Open-Endedness #LLMs
Contact: Elias Najarro
enaj@itu.dk
Emergence in Artificial Life
Investigating the emergence of artificial life forms known as virtual creatures using self-organisation and GPU accelerated simulations
#ALife #Emergence
Contact: Elias Najarro
enaj@itu.dk
Designing patterns to fool face recognition systems
The goal is combine use AI/ML methods to design patterns that can fool open source face detection and face recognition models and test them under real world conditions by painting/embroidering them.
#Design #Critical Tech #Optimisation
Contact: Elias Najarro
enaj@itu.dk
Drawing with Nature
Explore the expressivity and constraints of natural systems as generative systems
#Design #Generative
Contact: Elias Najarro
enaj@itu.dk
References: “Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Concepts”. Tian and Ha, 2022.
The Nature of Code: Simulating Natural Systems, Daniel Shiffman
Modelling neural growth
Build a generative model of how biological brains grow based on datasets from different species (such as C. elegans, fruit-fly, humans)
We will use recent generative models of graphs, such as Digress and Neural Developmental Programs, aiming at capturing
emergent features of neural growth
(related to structure and potentially function)
that simpler models cannot account for
(for example they often ignore neurogenesis
and do not scale)
Contact: Eleni Nisioti enis@itu.dk
Erwan Plantec erpl@itu.dk
Self-organising systems for robust visual perception
Explore the use self-organising systems such as Neural Cellular Automata for visual perception tasks such as image segmentation and representation of objects and scenes.
Contact: Milton Montero mlle@itu.dk
Self-organising systems for solving the ARC challenge
Explore the use self-organising systems such as Neural Cellular Automata for pattern generation following predefined rules as presented in the Abstract Reasoning Corpus challenge.
Contact: Milton Montero mlle@itu.dk