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Toward Dependable Multiple Path Planning for Autonomous Robots with Obstacle Avoidance and Congestion Control
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. (Robotics)ORCID iD: 0000-0002-4221-0853
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 and automation
Research subject
Electronics
Identifiers
URN: urn:nbn:se:mdh:diva-56593ISBN: 978-91-7485-541-8 (print)OAI: oai:DiVA.org:mdh-56593DiVA, id: diva2:1613959
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: 2025-02-09Bibliographically approved
List of papers
1. Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning
Open this publication in new window or tab >>Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning
2018 (English)In: Frontiers in Neurorobotics, E-ISSN 1662-5218, Vol. 12, article id 28Article in journal (Refereed) Published
Abstract [en]

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e, safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta* algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta* algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of these two fields results in a safe path planning algorithm, with a deterministic outcome, to navigate agents to their desired goals.

Place, publisher, year, edition, pages
FRONTIERS MEDIA SA, 2018
Keywords
navigation field. Theta star algorithm, dependability, multiple agents, path planning, dynamic environment
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-39973 (URN)10.3389/fnbot.2018.00028 (DOI)000434293100001 ()29928198 (PubMedID)2-s2.0-85048966124 (Scopus ID)
Available from: 2018-06-21 Created: 2018-06-21 Last updated: 2022-11-09Bibliographically approved
2. Dependable Navigation for Multiple Autonomous Robots with Petri Nets Based Congestion Control and Dynamic Obstacle Avoidance
Open this publication in new window or tab >>Dependable Navigation for Multiple Autonomous Robots with Petri Nets Based Congestion Control and Dynamic Obstacle Avoidance
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.

Keywords
Dependable path planning, Dipole field, Obstacle avoidance, Congestion control
National Category
Robotics and automation
Identifiers
urn:nbn:se:mdh:diva-56589 (URN)10.1007/s10846-022-01589-1 (DOI)000777399100001 ()2-s2.0-85127723096 (Scopus ID)
Available from: 2021-11-23 Created: 2021-11-23 Last updated: 2025-02-09Bibliographically approved
3. Multi-Path Planning for Autonomous Navigation of Multiple Robots in a Shared Workspace with Humans
Open this publication in new window or tab >>Multi-Path Planning for Autonomous Navigation of Multiple Robots in a Shared Workspace with Humans
2020 (English)In: 2020 6th International Conference on Control, Automation and Robotics ICCAR, Singapore, Singapore, 2020, p. 113-118, article id 9108082Conference paper, Published paper (Refereed)
Abstract [en]

Path finding for multiple robots is one of most important problems in robotics when to find a way to move robots from their starting positions to reach their respective goals without collisions. However, in the case of a complex environment with the presence of humans and other unpredictable moving objects, fixing a single path to the goal may lead to a situation where there are a lot of obstacles on the planned path and the robots may fail to realise the moving plan. To address this issue, a new approach of using multiple path planning where each robot has different options to choose its path to the goal is introduced in this paper. The information about planned moving paths are shared among the robots in the working domain, combined with obstacle avoidance constraints in local ranges, and formulated as an optimisation problem. Solution of the problem leads to the optimal moving plans of robots. The effectiveness of the proposed approach is demonstrated by experimental results.

Place, publisher, year, edition, pages
Singapore, Singapore: , 2020
National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-50943 (URN)10.1109/ICCAR49639.2020.9108082 (DOI)000591176900021 ()2-s2.0-85087052813 (Scopus ID)
Conference
2020 6th International Conference on Control, Automation and Robotics ICCAR, 20 Apr 2020, Singapore, Singapore
Projects
DPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2020-09-28 Created: 2020-09-28 Last updated: 2022-11-09Bibliographically approved
4. Decentralised Multi-Robot Path Planning with Obstacle Avoidance and Congestion Control Constraints
Open this publication in new window or tab >>Decentralised Multi-Robot Path Planning with Obstacle Avoidance and Congestion Control Constraints
(English)In: Article in journal, Editorial material (Refereed) Submitted
National Category
Robotics and automation
Identifiers
urn:nbn:se:mdh:diva-56590 (URN)
Available from: 2021-11-23 Created: 2021-11-23 Last updated: 2025-02-09Bibliographically approved

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Trinh, Lan Anh

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