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ROSEMAN (RObots SErving huMANs)

In ROSEMAN project components were developed for intelligent mobile robots which operate with humans in every day environments. The research had emphasis on the following areas: machine vision, control systems and learning, and teleoperation.

During the project a color vision system (COCOA) were developed for tracking multiple colored objects simultaneously. The system can be used, for example, to track a person based on her skin color, which was also demonstrated.

Neural network based evolutionary computation techniques were also developed for mobile robotics applications. During the project the stochastic evolutionary neuron migration process (SENMP) was developed which forms network structures, consisting of laterally interacting neurons, which are capable of controlling a mobile robot. The feasibility of the approach was demonstrated by evolving a navigation behavior for a real robot. The approach was also tested with non-Markov double-pole-balancing problem in which the method turn out to be the most efficient one among the tested methods.

Robot co-operation was also studied in this project. The emphasis was on robot formations - moving in formations and dynamic change of formations. This research utilized graph theoretical approaches for robot formations.

A localization method that uses color histograms and Icondensation algorithm was developed for mobile robots. The method worked well in environments where spatial locations and their color properties were related. Unfortunately, the office buildings today have very similar interior colors through out the buildings, which can make the color histogram based method unreliable.

The Samba-architecture was further developed for real robots. The Samba-architecture was previously used in RoboCup simulation league. In this project the modification of the Samba-architecture was used in the coffee serving system in which a mobile robot serves a cup of coffee, prepared by a robotic arm. An important part of the coffee serving system was the distributed XML-based state machine architecture developed during the project. The architecture provides a way to dynamically implement state machines, which utilize available robotic resources (e.g. sensors and actuators) from corresponding XML-descriptions. The state machine system can also be used in other domains than mobile robotics in a straightforward manner.

The development of modern communication systems opens interesting possibilities in mobile robotics. In this project a voice controlled teleoperation was demonstrated. By using a video conferencing software the user can control a remote mobile robot using simple high level speech commands. The operator can activate high level behaviors via speech and monitor the performance of the robot.


Mäenpää T., Tikanmäki A., Riekki J. and Röning J. (2004) A Distributed Architecture for Executing Complex Tasks with Multiple Robots, IEEE 2004 ICRA, International Conference on Robotics and Automation,Apr 26 - May 1, New Orleans, LA, USA. pdf

Haverinen J & Röning J (2002), A Stochastic Evolutionary Neuron Migration Process with Emerged Hebbian Dynamics, Proc. Artificial Life VIII: The 8th International Conference on the Simulation and Synthesis of Living Systems, Dec 9-1 3 , Sydney, NSW, Australia.

Haverinen J & Röning J (2002), Adaptation Through a Stochastic Evolutionary Neuron Migration Process (SENMP)Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2002), Sep 30 - Oct 4, EPFL, Lausanne, Switzerland. pdf

Pylkkö H, Riekki J & Röning J (2001) Real-time color-based tracking via a marker interface, Proc. IEEE International Conference of Robotics and Automation, May 21-26, Seoul, South Korea, 2:1214-1219.


voice controlled robot [5.2MB]. coffee service robot (a state machine demonstration) [9.3MB]. coffee service robot (edited version) [18.1MB]. SENMP [5.3MB].

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