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Dependable Navigation for Multiple Autonomous Robots with Petri Nets Based Congestion Control and Dynamic Obstacle Avoidance
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-4221-0853
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-5832-5452
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-5224-8302
2022 (English)In: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, ISSN 0921-0296, Vol. 104, no 4, article id 69Article in journal (Refereed) Published
Abstract [en]

In this paper, a novel path planning algorithm for multiple robots using congestion analysis and control is presented. The algorithm ensures a safe path planning solution by avoiding collisions among robots as well as among robots and humans. For each robot, alternative paths to the goal are realised. By analysing the travelling time of robots on different paths using Petri Nets, the optimal configuration of paths is selected. The prime objective is to avoid congestion when routing many robots into a narrow area. The movements of robots are controlled at every intersection by organising a one-by-one passing of the robots. Controls are available for the robots which are able to communicate and share information with each other. To avoid collision with humans and other moving objects (i.e. robots), a dipole field integrated with a dynamic window approach is developed. By considering the velocity and direction of the dynamic obstacles as sources of a virtual magnetic dipole moment, the dipole-dipole interaction between different moving objects will generate repulsive forces proportional to the velocity to prevent collisions. The whole system is presented on the widely used platform Robot Operating System (ROS) so that its implementation is extendable to real robots. Analysis and experiments are demonstrated with extensive simulations to evaluate the effectiveness of the proposed approach.

Place, publisher, year, edition, pages
2022. Vol. 104, no 4, article id 69
Keywords [en]
Dependable path planning, Dipole field, Obstacle avoidance, Congestion control
National Category
Robotics
Identifiers
URN: urn:nbn:se:mdh:diva-56589DOI: 10.1007/s10846-022-01589-1ISI: 000777399100001Scopus ID: 2-s2.0-85127723096OAI: oai:DiVA.org:mdh-56589DiVA, id: diva2:1613950
Available from: 2021-11-23 Created: 2021-11-23 Last updated: 2022-11-02Bibliographically approved
In thesis
1. Toward Dependable Multiple Path Planning for Autonomous Robots with Obstacle Avoidance and Congestion Control
Open this publication in new window or tab >>Toward Dependable Multiple Path Planning for Autonomous Robots with Obstacle Avoidance and Congestion Control
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Over decades, automatic robots that are pre-programmed to perform repetitive tasks in industrial production has been reaching the cutting edge of technology. There is emerging the next development with autonomous control, where a robot is able to have some levels of its own decision, i.e. self-governing, without direct controls from humans. This brings autonomous robots extensively applicable not only in industry but also in commonly accessible services in our daily life such as self-driving cars, automated health care, or entertainment. Yet, one of the backbone of the robotic system, the navigation and path planning, has to face more and more challenges including unstructured environments, uncertainty of moving objects, coexist with humans, and multiple robotic agents. Aiming toward a dependable, i.e. available, reliable, and safe, path planning system to overcome such challenges, this thesis proposes the development of multiple path planning along with obstacle avoidance and congestion control algorithms. At first, a novel dipole flow field, which is constructed from a flow field to drive robots to their goals and a dipole field to push robots far away from potential collision directions, is proposed. The algorithm is efficient in implementation yet is able to overcome the drawback of conventional field-based approach, which is easily trapped by a local optimisation of energy functions.  Secondly, a congestion control mechanism with Petri net is developed to synchronise the movement of robots when they enter in a cross or narrow area. Different Petri nets are evaluated to find the optimal configuration to reduce the traffic jam through possible conflict regions. In the next contribution, the dead- or live-lock problem of a path planning system is addressed. The solution is based on multiple path planning where each robot has alternative paths to the goal. All robots in the same working space communicate with each other to update their locations and paths so that the appropriate configuration can be chosen to avoid potential deadlocks. The algorithm also takes into account the obstacle avoidance so that the robots are able to avoid mutual collisions as well as collisions with unexpected moving objects like humans. Finally, a distributed multiple path planning algorithm is implemented to help the system to deal with some level of failures, which happens when the central controlling system of robots stops working or a part of communication network between the robots is unexpectedly disconnected. The proposed approaches have been evaluated by extensive experiments to show their effectiveness in addressing collisions, congestion, as well as deadlocks. The implementation of the algorithms has been performed on widely accessible platform, robot operating system (ROS) and transferred into real robots.

Place, publisher, year, edition, pages
Västerås: Mälardalen university, 2022
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 352
National Category
Robotics
Research subject
Electronics
Identifiers
urn:nbn:se:mdh:diva-56593 (URN)978-91-7485-541-8 (ISBN)
Public defence
2022-01-18, U2-024 and virtually on Zoom/Teams, Mälardalens högskola, Västerås, 14:00 (English)
Opponent
Supervisors
Available from: 2021-11-24 Created: 2021-11-24 Last updated: 2021-12-28Bibliographically approved

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Trinh, LanAnhEkström, MikaelCuruklu, Baran

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