Hierarchical Task Assignment and Path Finding with Limited Communication for Robot Swarms

Dario Albani; Wolfgang Hönig; Daniele Nardi; Nora Ayanian; Vito Trianni

doi:10.3390/app11073115

Hierarchical Task Assignment and Path Finding with Limited Communication for Robot Swarms

Applied Sciences ◽

10.3390/app11073115 ◽

2021 ◽

Vol 11 (7) ◽

pp. 3115

Author(s):

Dario Albani ◽

Wolfgang Hönig ◽

Daniele Nardi ◽

Nora Ayanian ◽

Vito Trianni

Keyword(s):

Path Planning ◽

Large Scale ◽

Statistical Significance ◽

Task Assignment ◽

Task Demands ◽

Service Needs ◽

Limited Communication ◽

Robot Swarms ◽

Robot Systems ◽

Optimal Allocations

Complex service robotics scenarios entail unpredictable task appearance both in space and time. This requires robots to continuously relocate and imposes a trade-off between motion costs and efficiency in task execution. In such scenarios, multi-robot systems and even swarms of robots can be exploited to service different areas in parallel. An efficient deployment needs to continuously determine the best allocation according to the actual service needs, while also taking relocation costs into account when such allocation must be modified. For large scale problems, centrally predicting optimal allocations and movement paths for each robot quickly becomes infeasible. Instead, decentralized solutions are needed that allow the robotic system to self-organize and adaptively respond to the task demands. In this paper, we propose a distributed and asynchronous approach to simultaneous task assignment and path planning for robot swarms, which combines a bio-inspired collective decision-making process for the allocation of robots to areas to be serviced, and a search-based path planning approach for the actual routing of robots towards tasks to be executed. Task allocation exploits a hierarchical representation of the workspace, supporting the robot deployment to the areas that mostly require service. We investigate four realistic environments of increasing complexity, where each task requires a robot to reach a location and work for a specific amount of time. The proposed approach improves over two different baseline algorithms in specific settings with statistical significance, while showing consistently good results overall. Moreover, the proposed solution is robust to limited communication and robot failures.

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Optimization-based approach to path planning for closed chain robot systems

International Journal of Applied Mathematics and Computer Science ◽

10.2478/v10006-011-0052-8 ◽

2011 ◽

Vol 21 (4) ◽

pp. 659-670 ◽

Cited By ~ 9

Author(s):

Wojciech Szynkiewicz ◽

Jacek Błaszczyk

Keyword(s):

Path Planning ◽

Large Scale ◽

Inequality Constraints ◽

Optimization Techniques ◽

Planning Problem ◽

Closed Chain ◽

Robot Systems ◽

Equality And Inequality Constraints ◽

Primal Dual ◽

The Given

Optimization-based approach to path planning for closed chain robot systems An application of advanced optimization techniques to solve the path planning problem for closed chain robot systems is proposed. The approach to path planning is formulated as a "quasi-dynamic" NonLinear Programming (NLP) problem with equality and inequality constraints in terms of the joint variables. The essence of the method is to find joint paths which satisfy the given constraints and minimize the proposed performance index. For numerical solution of the NLP problem, the IPOPT solver is used, which implements a nonlinear primal-dual interior-point method, one of the leading techniques for large-scale nonlinear optimization.

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Dietary Patterns: A New Therapeutic Approach for Depression?

Current Pharmaceutical Biotechnology ◽

10.2174/1389201019666180925122116 ◽

2019 ◽

Vol 20 (2) ◽

pp. 123-129 ◽

Cited By ~ 3

Author(s):

Mariana Jesus ◽

Tânia Silva ◽

César Cagigal ◽

Vera Martins ◽

Carla Silva

Keyword(s):

Depressive Symptoms ◽

Dietary Patterns ◽

Large Scale ◽

Randomized Clinical Trials ◽

Dietary Intervention ◽

Common Mental Disorder ◽

Controlled Trial ◽

Statistical Significance ◽

Inverse Association ◽

The Impact

Introduction: The field of nutritional psychiatry is a fast-growing one. Although initially, it focused on the effects of vitamins and micronutrients in mental health, in the last decade, its focus also extended to the dietary patterns. The possibility of a dietary cost-effective intervention in the most common mental disorder, depression, cannot be overlooked due to its potential large-scale impact. Method: A classic review of the literature was conducted, and studies published between 2010 and 2018 focusing on the impact of dietary patterns in depression and depressive symptoms were included. Results: We found 10 studies that matched our criteria. Most studies showed an inverse association between healthy dietary patterns, rich in fruits, vegetables, lean meats, nuts and whole grains, and with low intake of processed and sugary foods, and depression and depressive symptoms throughout an array of age groups, although some authors reported statistical significance only in women. While most studies were of cross-sectional design, making it difficult to infer causality, a randomized controlled trial presented similar results. Discussion: he association between dietary patterns and depression is now well-established, although the exact etiological pathways are still unknown. Dietary intervention, with the implementation of healthier dietary patterns, closer to the traditional ones, can play an important role in the prevention and adjunctive therapy of depression and depressive symptoms. Conclusion: More large-scale randomized clinical trials need to be conducted, in order to confirm the association between high-quality dietary patterns and lower risk of depression and depressive symptoms.

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A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327910999200723164502 ◽

2020 ◽

Vol 10 ◽

Author(s):

Abdelhady M. Naguib ◽

Shahzad Ali

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Path Planning ◽

Sensor Node ◽

Large Scale ◽

Performance Metrics ◽

Wireless Sensor ◽

Anchor Node ◽

Mobile Anchor ◽

Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

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COVID-19 and Its Symptoms’ Panoply: A Case-Control Study of 919 Suspected Cases in Locked-Down Ovar, Portugal

Portuguese Journal of Public Health ◽

10.1159/000514925 ◽

2021 ◽

pp. 1-8

Author(s):

Regina Sá ◽

Tiago Pinho-Bandeira ◽

Guilherme Queiroz ◽

Joana Matos ◽

João Duarte Ferreira ◽

...

Keyword(s):

Large Scale ◽

Case Control Study ◽

Statistical Significance ◽

Case Control ◽

Case Definition ◽

Suspected Case ◽

Risk Characteristics ◽

Increased Risk ◽

Wide Range ◽

Control Study

Background: Ovar was the first Portuguese municipality to declare active community transmission of SARS-CoV-2, with total lockdown decreed on March 17, 2020. This context provided conditions for a large-scale testing strategy, allowing a referral system considering other symptoms besides the ones that were part of the case definition (fever, cough, and dyspnea). This study aims to identify other symptoms associated with COVID-19 since it may clarify the pre-test probability of the occurrence of the disease. Methods: This case-control study uses primary care registers between March 29 and May 10, 2020 in Ovar municipality. Pre-test clinical and exposure-risk characteristics, reported by physicians, were collected through a form, and linked with their laboratory result. Results: The study population included a total of 919 patients, of whom 226 (24.6%) were COVID-19 cases and 693 were negative for SARS-CoV-2. Only 27.1% of the patients reporting contact with a confirmed or suspected case tested positive. In the multivariate analysis, statistical significance was obtained for headaches (OR 0.558), odynophagia (OR 0.273), anosmia (OR 2.360), and other symptoms (OR 2.157). The interaction of anosmia and odynophagia appeared as possibly relevant with a borderline statistically significant OR of 3.375. Conclusion: COVID-19 has a wide range of symptoms. Of the myriad described, the present study highlights anosmia itself and calls for additional studies on the interaction between anosmia and odynophagia. Headaches and odynophagia by themselves are not associated with an increased risk for the disease. These findings may help clinicians in deciding when to test, especially when other diseases with similar symptoms are more prevalent, namely in winter.

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Multi-UAVs cooperative task assignment and path planning scheme

Journal of Physics Conference Series ◽

10.1088/1742-6596/1856/1/012016 ◽

2021 ◽

Vol 1856 (1) ◽

pp. 012016

Author(s):

Xiaoyu Du ◽

Qicheng Guo ◽

Hui Li ◽

Yanyu Zhang

Keyword(s):

Path Planning ◽

Task Assignment ◽

Planning Scheme

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Decentralized Task and Path Planning for Multi-Robot Systems

IEEE Robotics and Automation Letters ◽

10.1109/lra.2021.3068103 ◽

2021 ◽

Vol 6 (3) ◽

pp. 4337-4344

Author(s):

Yuxiao Chen ◽

Ugo Rosolia ◽

Aaron D. Ames

Keyword(s):

Path Planning ◽

Robot Systems ◽

Multi Robot

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Safe Path Planning Algorithms for Mobile Robots Based on Probabilistic Foam

Sensors ◽

10.3390/s21124156 ◽

2021 ◽

Vol 21 (12) ◽

pp. 4156

Author(s):

Luís B. P. Nascimento ◽

Dennis Barrios-Aranibar ◽

Vitor G. Santos ◽

Diego S. Pereira ◽

William C. Ribeiro ◽

...

Keyword(s):

Path Planning ◽

Mobile Robots ◽

Configuration Space ◽

Autonomous Robot ◽

Breadth First Search ◽

Propagation Process ◽

Robot Systems ◽

And Performance ◽

Safe Path ◽

High Clearance

The planning of safe paths is an important issue for autonomous robot systems. The Probabilistic Foam method (PFM) is a planner that guarantees safe paths bounded by a sequence of structures called bubbles that provides safe regions. This method performs the planning by covering the free configuration space with bubbles, an approach analogous to a breadth-first search. To improve the propagation process and keep the safety, we present three algorithms based on Probabilistic Foam: Goal-biased Probabilistic Foam (GBPF), Radius-biased Probabilistic Foam (RBPF), and Heuristic-guided Probabilistic Foam (HPF); the last two are proposed in this work. The variant GBPF is fast, HPF finds short paths, and RBPF finds high-clearance paths. Some simulations were performed using four different maps to analyze the behavior and performance of the methods. Besides, the safety was analyzed considering the new propagation strategies.

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Research Progress on Synergistic Technologies of Agricultural Multi-Robots

Applied Sciences ◽

10.3390/app11041448 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1448

Author(s):

Wenju Mao ◽

Zhijie Liu ◽

Heng Liu ◽

Fuzeng Yang ◽

Meirong Wang

Keyword(s):

Path Planning ◽

Formation Control ◽

Research Progress ◽

Hybrid Architecture ◽

Labor Costs ◽

Robot System ◽

System Architectures ◽

Research Results ◽

Robot Systems ◽

Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

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