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Decentralized exploration and map building based on multiple autonomous UAVs

As the autonomy and AI technologies are evolving, the challenges in developing complete autonomous missions remain, especially in extreme environments with perceptual degradation, difficult terrain, high-risk operations and so on. The focus of this Master Thesis is towards identifying the key modules used for autonomous exploration and map building with multiple UAVs, and developing important modules that are currently missing or under-perform in extreme environment scenarios. One of them is the ability to merge multiple robots' 3D point cloud maps, in order to have a robust and efficient path planning algorithm. Another one is the global pose estimation algorithms in featureless and GPS-denied environments.

$!userInfo.givenName Nikos Stathoulopoulos

Nikos Stathoulopoulos, - Master Student

Rapidly-Exploring Random Trees for real-time combined Exploration and Path Planning

The initial work in this master thesis will be towards solving the fundamental problems with ERRT in speeding up the multi-path planner, and by adding integration through ROS with mapping and frontier generation modules, such that ERRT can directly take online map updates from an occupancy mapper such as OctoMap or VoxBlox.
Once the framework is operational, initial testing in real-time simulations such as Gazebo can be performed as a stepping stone towards real experiments.
​The thesis can be progressed by the integration of multi-agent exploration behavior into the framework and by adding novel techniques such as adaptive sampling.

Kalle Löfgren, - Master student

A Soft Robotics Inspired Unmanned Aerial Platform

Soft robotics is a fast growing area within the robotic field that is expected to have a significant rise in the upcoming years. The proposal for this master thesis is to design, develop and control an unmanned aerial vehicle (UAV) based on principles from the area of soft robotics.

$!userInfo.givenName Jim Västanälv

Jim Västanälv, - Master student

Development, Control and Investigation of a Robotic Exoskeleton for Astronaut Back Support

The purpose of this master thesis is to design, develop, control and investigate the use of a back exoskeleton via the use of compliant actuators for providing adjustable operation in terms of assistance and resistance during use. Using a combination of rigid and compliant mechanisms that support the back’s natural motion, while providing an adjustable force exertion level, the exoskeleton will be able to either enable the reduction of energy exertion, loading and fatigue during post-travel rehabilitation.

Evert Häggman, - Master student

Available Master's thesis projects

If you are interested to make a Master thesis with us please contact indicated persons in the available projects below or send an email to We would like to discuss your ideas with you and build a customised thesis that will fit your ambition 100%.


Master Students

Evert Häggman - Development, Control and Investigation of a Robotic Exoskeleton for Astronaut Back Support
Niklas Dahlquist - Generation of Behavior Trees for Dynamical Agents Based on Market Based Task Allocation
Clement Petit - Mapping and Path planning for aerial vehicles in SubT environments
Jonathan Olsson - Detect Anomalies in Shapes Using Machine Learning Techniques
Alkis Sigkounas - Multi Agent Exploration with Reinforcement Learning
Enrico Giacomini - Design, Modeling and Control of a Thrust Based UAV
Vignesh Kottayam Viswanathan - Cooperative Navigation of Spacecrafts in proximity of small bodies
Tommaso Gasparetto - Docking mechanism design and development, detection and guidance for space robots
Eric Brune - AI empowered feature based detection and tracking for visual servoing of satellites
Scott Fredriksson - Design, Development and Control of a Quadruped Robot
Jerker Bergström - UAV path planning and collision avoidance in unknown environments
Matteo Terreran (Aalto Uni)- Machine Learning and Computer Vision for Aerial manipulation
Maros Hladky (Aalto Uni) - Vision Based Attitude Control
Issouf Ouattara (Aalto Uni) - Semi-autonomous drone System for Mapping and Measuring of Agricultural Fields and Forest Stands
Olivier Struckmeier (Aalto Uni) - Generating Explanations of Robot Policies in Continuous State Spaces 
Usama Tariq - Robotic Grasping of Large Objects for Collaborative Manipulation
Anna Costalonga - Modeling and Control of a novel PMA enabled robotic arm
Elias Small - Tilt Rotor: Development and Control
David Wuthier (EPFL, Switzerland) - Aerial Manipulation
Nicola Dal Lago (University of Padova) - Aerial Mapping
Christoffer Carholt - Single Rotor UAV
Adrian Lindqvist - Modeling and Experimental Evaluation of a Tilt Rotor Aircraft
Rickard Nyberg - Development and Control of Unammaned Ground Vehicles (UGVs), now at VOLVO cars
Emil Fresk  -   Modeling, Control and Experimentation of a Variable Pitch Quadrotor
Ivan Monzon Catalan  -   Development of a ROS enabled Quadrotor
Theodoros Giannakas  -  Model Predictive Control of a Pulp & Paper Refiner