Category: Uncategorized
Manipulation of Granular Materials by Learning Particle Interactions
In this work we propose to use a Graph Neural Network (GNN) surrogate model to learn the particle interactions of granular materials. We perform planning of manipulation trajectories with the learnt surrogate model to arrange the material into a desired configuration.
From imitation to self-exploration: Learning object manipulation skills
Robotics Seminar Series. Second Session 2022 – 1st April 2022. Speaker: Seungsu Kim
Understanding Capsule Networks: will they overcome Convolutional Neural Networks?
Robotics Seminar Series. First Session 2022 – 17th March 2022. Speaker: Riccardo Renzulli
Defense of doctoral thesis “Towards Robust 6-DoF Multi-Finger Grasping in Clutter with Explicit Scene Understanding”, M.Sc.(Tech.) Jens Lundell
Defense of doctoral thesis. 25.02.2022, 12:00-15:00. Doctoral candidate: M.Sc. Jens Lundell
Building a quadruped robot for reinforcement learning research
The goal of this project is to build the open-sourced quadruped robot called Real-Ant. To start with, the 3D models and the codes for the microcontroller as well as serial port communication are available for the robot. So the first task will be to print the components, assemble the robot and test the available codes on the robot. Then in the second stage, we will modify the robot to make it more robust so that it can tolerate mild shocks and can be run for an extended period of time without the need of tightening the screws or replacing the components. For example, we can think of adding soft legs, cushions etc. to protect the belly and the actuators. In addition, we can also simplify the design so that it can be repaired quickly if required.
Master Thesis on the Co-Adaptation of Robots
The goal of this Master thesis is to develop simulation tools necessary to evaluate co-adaptation techniques, and to develop new approaches for learning the behaviour and design of robots using deep learning and deep reinforcement learning.
Master Thesis on “Safe Constrained Differential Dynamic Programming”
In this thesis, an extensive investigation of constrained DDP methods will be performed and the major selected ones will be implemented in simulation environment for trajectory optimizations of different robots such as a simple point robot, 2D car-like robot, 3D quadrotor robot and cart-pole system. In this context, the methods will be compared in terms of convergence speed, computational complexity, sensitivity to initializations and parameter selections.
Evolving-Graph Gaussian Processes
Robotics Seminar Series. Fifth Session 2021 – 15th October 2021. Speaker: David Blanco Mulero
Co-Adaptation of Robot Behaviour and Morphology with Deep Reinforcement Learning
Robotics Seminar Series. Fourth Session 2021 – 17th September 2021. Speaker: Kevin Sebastian Luck
Season-invariant GNSS-denied visual localization for UAVs
This repository contains data and code for manuscript J. Kinnari, F. Verdoja, V. Kyrki “Season-invariant GNSS-denied visual localization for UAVs”.