QUADRIVIO PRO - ATV PATH PLANNING ON PARTIALLY KNOWN TERRAINS (ongoing project)

PROJECT ABSTRACT:

The popularity of the research of the unmanned ground vehicles has been increased recently due to their usefulness in different operation environments. Planetary explorations, search and rescue missions in hazard areas, surveillance, humanitarian de-mining, as well as agriculture applications such as pruning vine and fruit trees, represent possible fields of using autonomous vehicles in natural environments. Differently from the case of indoor mobile robotics where exclusively flat terrains are considered, the outdoor robotics deals with all possible natural terrains. The unstructured environment and the terrain roughness including dynamic obstacles and poorly traversable terrains pose a challenging problem for the autonomy of the vehicle. The proposed project aims at finding and implementing reliable algorithm for ATV path planning on rough terrains. The algorithm will deal with terrain irregularaties so that the vehicle finds smoother terrain regions while reaching the final target. Taking smoother regions provides a broder manevrability space from which the vehicle is able to preserve stability, where stability is refleceted by preventing the vehicle from the sideslip and rolover. A broder manevrability space gives a possibillity to move with high speeds which might be important in a variaty of applications. In addition, the proposed algorithm will deal with partially known or completely uknown terrains which is a chalanging task for real time implementation of a mobile vehicle moving in outdoor environments.

In the proposed work, we will utilized the model predictive control for motion planning on rough terrains. Model predictive control is a framework of choice since such an optimization allows for taking into account different nonlinear constraints during the task execution. Special focus will be on the integration of the vehicle dynamics into the motion planner optimization setup, which gives a reliable trajectory generator when an appropriate kinematic model might not sufficiently describe the vehicle behavior. Such a case might be the result of high vehicle speeds on rough terrains, which might be of interest in a variety of applications. In addition, the motion planning optimization setup will take into account a newly appearing obstacles and terrain shapes sensed by the local sensors, which requires an appropriate cost-to-go map re-computation. This extension might be of scientific interest, since the currently state-of-the art algorithms, such are D* -like variants, consider only point-wise mobile robot, and they do not include vehicle model into the path planning algorithm. Merging an MPC optimization framework with D* or its slight modifications might be an interesting result in comparison to the state of the art algorithms.

COMMENT: This project is the result of a cooperation between Politecnico di Milano and Faculty of Electrical Engineering Sarajevo.

PARTICIPANTS:

• Italy: Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Mechatronics and Robotics Laboratory for Innovation (MERLIN)
• Bosnia and Herzegovina: University of Sarajevo, Department for Automatic Control, Lab for Automatic Decision and Control Systems

MORUS - UNMANNED SYSTEM FOR MARITIME SECURITY AND ENVIRONMENTAL MONITORING (ongoing project)

PROJECT ABSTRACT:

The main goal of MORUS project is a design and development of a fully operational complex robotic system prototype comprised of an Unmanned Aerial Vehicle (UAV) and Unmanned Underwater Vehicle (UUV) capable of autonomous and cooperative mission executions related to environmental, border and port security. The proposed research is in internationally competitive field with the main objective to design and develop autonomous aerial and marine robotic system, capable of collective engagement in missions taking place in dynamic and nondeterministic environments. The design will focus mainly on payload enhancement and UAV autonomy which is mandatory for UUV transport. Besides that, a docking system and cooperative control algorithms will be developed enabling autonomous deployment, re-deployment and data exchange at the open sea. Operating environment of the proposed prototype is an unknown, uncertain and remote, i.e. far from a human operator. Therefore, a whole set of novel cooperative control algorithms, combined with augmented human machine interface, will be designed and implemented in order to ensure safety and recoverability of the described system. Having said that, objectives of the MORUS project are summarised as follows: 1. Design and construction of an UAV with docking and transportation mechanism, 2. Visual feedback based docking and gripping algorithm, 3. Design of augmented and easy to operate human machine interface for simultaneous control of aerial and marine robots, 4. Enhancement of the autonomous navigation capabilities and operational supportability in remote locations with few or no local support, 5. Agile UUV redeployment through cooperation with an UAV, 6. Enable data exchange between the UUV and UAV through cooperative control and estimation.

COMMENT: This project is funded by NATO within the Science for Piece and Security Programm (SPS Programme).

PARTICIPANTS:

• Croatia: University of Zagreb, Faculty of Electrical Engineering and Computing, Department of Control and Computer Engineering, Laboratory for Robotics and Intelligent Control Systems (LARICS)
• Croatia: University of Zagreb, Faculty of Electrical Engineering and Computing, Department of Control and Computer Engineering, Laboratory for Underwater Systems and Technologies, (LABUST)
• Irland: University of Limerick, Marine Robotics Research Centre, (MRRC)
• Croatia: University of Dubrovnik
• Bosnia and Herzegovina: University of Sarajevo, Faculty of Electrical Engineering, Department for Automatic Control, Lab for Automatic Decision and Control Systems