Example

In 2015 Tampere University of Technology started new profiling initiative in the field of “Robotics and Intelligent Machines” resulting to significant profiling funding from Academy of Finland. A part of the profiling process is a TUT funded Flagship project on collaborative heavy machine worksites that combines researchers from the four TUT departments: Intelligent Hydraulics and Automation (IHA), Automation Science and Engineering (ASE), Signal Processing (SGN) and Mechanical Engineering and Industrial Systems (MEI). The goal of this project is to foster multidisciplinary research in the field of heavy field robotics.

Videos of the project demonstrations:

People

Risto Ritala E-mail Professor (ASE), coordinator of the project
Joni Kämäräinen E-mail Professor (SGN)
Jussi Halme E-mail PhD student (MEI)
Eero Heinanen E-mail Graduate student (ASE)
Kari Koskinen E-mail Professor (MEI)
Minna Lanz E-mail Professor (MEI)
Heikki Huttunen E-mail Adjunct Professor (SGN)
Reza Ghabcheloo E-mail Professor (IHA)
Kalevi Huhtala E-mail Professor (IHA)
Antti Hietanen E-mail PhD student (SGN)
Mikko Lauri E-mail Post-doc researcher (ASE)
Antti Kolu E-mail PhD student (IHA)
Alireza Changizi E-mail PhD student (MEI)
Mohammad Mohammadi Aref E-mail PhD student (IHA)

Selected Publications

Meeting a deadline: shortest paths on stochastic directed acyclic graphs with information gathering

By M. Lauri, A. Ropponen and R. Ristala in Annals of Mathematics and Artificial Intelligence, September, pp. 1-34, 2016.

We consider the problem of an agent traversing a directed graph with the objective of maximizing the probability of reaching a goal node before a given deadline. Only the probability of the travel times of edges is known to the agent.

Vision-Guided Autonomous Forklift

By Mohammad M. Aref, Reza Ghabcheloo, Antti Kolu, and Jouni Mattila in 25th Conference on Robotics in Alpe-Adria-Danube Region (RAAD) 2016.

This paper shows how a vehicle controller is capable of breaking down high-level messages into piecewise commands for different software modules of the vehicle. It also preserves seamless cooperation of the modules for a successful pallet-picking mission. Best Robot Application Paper Award

BibTex 

A Mapping Method Tolerant to Calibration and Localization Errors Based on Tilting 2D Laser Scanner

By A. Kolu, M. Lauri, M. Hyvönen, R. Ghabcheloo and K. Huhtala. In European Control Conference (ECC) 2015.

We propose a macro–micro visual mobile manipulation method. A smooth switching logic navigates the robot to pick an object.

BibTex 

A Multistage Controller with Smooth Switching for Autonomous Pallet Picking

By By Mohammad M. Aref, Reza Ghabcheloo, Antti Kolu, and Jouni Mattila. In IEEE International Conference on Robotics and Automation (ICRA) 2014.

We propose a macro–micro visual mobile manipulation method. A smooth switching logic navigates the robot to pick an object.

BibTex 

Links

Public Appearance

TUT Robotics and Intelligent Machines (TUT-RIM) researchers in robot grasping workshop
The TUT Flagship project "Robotics and Intelligent Machines" started by four departments

Other Authors and Teams

Georgia Tech Institute for Robotics and Intelligent Machines
The Robotics Institute of Carnegie-Mellon