Special Issue "Agents and Robots for Reliable Engineered Autonomy"

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708).

Deadline for manuscript submissions: closed (14 March 2021).

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Rafael C. Cardoso
E-Mail Website
Guest Editor
Department of Computer Science, The University of Manchester, Manchester, UK
Interests: multi-agent systems; automated planning; formal verification
Dr. Angelo Ferrando
E-Mail Website
Guest Editor
Department of Computer Science, University of Genova, Genoa, Italy
Interests: multi-agent systems; runtime verification; software engineering
Dr. Daniela Briola
E-Mail Website
Guest Editor
Department of IT, Systems and Communications, University of Milano-Bicocca, 20126 Milano MI, Italy
Interests: multi-agent systems; field monitoring; software engineering
Dr. Claudio Menghi
E-Mail Website
Guest Editor
Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg L-1855, Luxembourg
Interests: cyber-physical systems; software engineering; formal methods
Mr. Tobias Ahlbrecht
E-Mail Website
Guest Editor
Department of Informatics, Clausthal University of Technology, Clausthal-Zellerfeld, Germany
Interests: multi-agent systems; agent-oriented software engineering; explainable AI

Special Issue Information

Dear Colleagues,

Autonomous agents are a well-established area that has been researched for decades, both from a design and implementation viewpoint. Nonetheless, the application of agents in real world scenarios is largely adopted when logical distribution is needed, while still limited when physical distribution is necessary. In parallel, robots are no longer used only in industrial applications but are instead being applied to an increasing number of domains, ranging from robotic assistants to search and rescue. Robots in these applications often benefit from (or require) some level (semi or full) of autonomy. Thus, multiagent solutions can be exploited in robotic scenarios, considering their strong similarity both in terms of logical distribution and interaction among autonomous entities.

The autonomous behaviour responsible for decision-making should (ideally) be verifiable since these systems are expensive to produce and are often deployed in safety-critical situations. Thus, verification and validation are important and necessary steps towards providing assurances about the reliability of autonomy in these systems. This Special Issue aims to bring together researchers from the autonomous agents, software engineering and the robotics communities, as combining knowledge coming from these two research areas may lead to innovative approaches that solve complex problems related with the verification and validation of autonomous robotic systems. Consequently, we encourage submissions that combine agents, robots and verification, but we also welcome papers focused on one of these areas, as long as their applicability to the other areas is clear.

The Special Issue seeks original contributions that address but are not limited to the following topics:

  • Agent-based modular architectures applicable to robots;
  • Agent oriented software engineering to model high-level control in robotic development;
  • Agent programming languages and tools for developing robotic or intelligent autonomous systems;
  • Coordination, interaction and negotiation protocols for agents and robots;
  • Distributed problem solving and automated planning in autonomous systems;
  • Fault tolerance, health-management and long-term autonomy;
  • Real world applications of autonomous agents and multiagent systems in robotics;
  • Real-time multiagent systems;
  • Reliable software engineering of autonomy;
  • Runtime verification of autonomous agents and robotic systems;
  • Task and resource allocation in multirobot systems;
  • Verification and validation of autonomous systems;
  • Testing and simulation tools and techniques for autonomous or robotic systems;
  • Self-healing entities and systems.

This Special Issue is based on the First International Workshop on “Agents and Robots for reliable Engineered Autonomy (AREA)”, https://area2020.github.io/, co-located with ECAI 2020. Authors of selected papers from the workshop are invited to submit an extended version of their text and completely new submissions from the community are also welcome.

Dr. Rafael C. Cardoso
Dr. Angelo Ferrando
Dr. Daniela Briola
Dr. Claudio Menghi
Mr. Tobias Ahlbrecht
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Sensor and Actuator Networks is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multiagent systems
  • formal methods
  • robotics
  • software engineering

Published Papers (6 papers)

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Editorial

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Editorial
Special Issue: Agents and Robots for Reliable Engineered Autonomy
J. Sens. Actuator Netw. 2021, 10(3), 47; https://doi.org/10.3390/jsan10030047 - 13 Jul 2021
Cited by 1 | Viewed by 379
Abstract
The study of autonomous agents is a well-established area that has been researched for decades, both from a design and implementation viewpoint [...] Full article
(This article belongs to the Special Issue Agents and Robots for Reliable Engineered Autonomy)

Research

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Article
Hybrid Verification Technique for Decision-Making of Self-Driving Vehicles
J. Sens. Actuator Netw. 2021, 10(3), 42; https://doi.org/10.3390/jsan10030042 - 29 Jun 2021
Cited by 1 | Viewed by 506
Abstract
The evolution of driving technology has recently progressed from active safety features and ADAS systems to fully sensor-guided autonomous driving. Bringing such a vehicle to market requires not only simulation and testing but formal verification to account for all possible traffic scenarios. A [...] Read more.
The evolution of driving technology has recently progressed from active safety features and ADAS systems to fully sensor-guided autonomous driving. Bringing such a vehicle to market requires not only simulation and testing but formal verification to account for all possible traffic scenarios. A new verification approach, which combines the use of two well-known model checkers: model checker for multi-agent systems (MCMAS) and probabilistic model checker (PRISM), is presented for this purpose. The overall structure of our autonomous vehicle (AV) system consists of: (1) A perception system of sensors that feeds data into (2) a rational agent (RA) based on a belief–desire–intention (BDI) architecture, which uses a model of the environment and is connected to the RA for verification of decision-making, and (3) a feedback control systems for following a self-planned path. MCMAS is used to check the consistency and stability of the BDI agent logic during design-time. PRISM is used to provide the RA with the probability of success while it decides to take action during run-time operation. This allows the RA to select movements of the highest probability of success from several generated alternatives. This framework has been tested on a new AV software platform built using the robot operating system (ROS) and virtual reality (VR) Gazebo Simulator. It also includes a parking lot scenario to test the feasibility of this approach in a realistic environment. A practical implementation of the AV system was also carried out on the experimental testbed. Full article
(This article belongs to the Special Issue Agents and Robots for Reliable Engineered Autonomy)
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Article
A Double-Level Model Checking Approach for an Agent-Based Autonomous Vehicle and Road Junction Regulations
J. Sens. Actuator Netw. 2021, 10(3), 41; https://doi.org/10.3390/jsan10030041 - 25 Jun 2021
Cited by 1 | Viewed by 424
Abstract
Usually, the design of an Autonomous Vehicle (AV) does not take into account traffic rules and so the adoption of these rules can bring some challenges, e.g., how to come up with a Digital Highway Code which captures the proper behaviour of an [...] Read more.
Usually, the design of an Autonomous Vehicle (AV) does not take into account traffic rules and so the adoption of these rules can bring some challenges, e.g., how to come up with a Digital Highway Code which captures the proper behaviour of an AV against the traffic rules and at the same time minimises changes to the existing Highway Code? Here, we formally model and implement three Road Junction rules (from the UK Highway Code). We use timed automata to model the system and the MCAPL (Model Checking Agent Programming Language) framework to implement an agent and its environment. We also assess the behaviour of our agent according to the Road Junction rules using a double-level Model Checking technique, i.e., UPPAAL at the design level and AJPF (Agent Java PathFinder) at the development level. We have formally verified 30 properties (18 with UPPAAL and 12 with AJPF), where these properties describe the agent’s behaviour against the three Road Junction rules using a simulated traffic scenario, including artefacts like traffic signs and road users. In addition, our approach aims to extract the best from the double-level verification, i.e., using time constraints in UPPAAL timed automata to determine thresholds for the AVs actions and tracing the agent’s behaviour by using MCAPL, in a way that one can tell when and how a given Road Junction rule was selected by the agent. This work provides a proof-of-concept for the formal verification of AV behaviour with respect to traffic rules. Full article
(This article belongs to the Special Issue Agents and Robots for Reliable Engineered Autonomy)
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Article
A Programming Approach to Collective Autonomy
J. Sens. Actuator Netw. 2021, 10(2), 27; https://doi.org/10.3390/jsan10020027 - 19 Apr 2021
Cited by 1 | Viewed by 494
Abstract
Research and technology developments on autonomous agents and autonomic computing promote a vision of artificial systems that are able to resiliently manage themselves and autonomously deal with issues at runtime in dynamic environments. Indeed, autonomy can be leveraged to unburden humans from mundane [...] Read more.
Research and technology developments on autonomous agents and autonomic computing promote a vision of artificial systems that are able to resiliently manage themselves and autonomously deal with issues at runtime in dynamic environments. Indeed, autonomy can be leveraged to unburden humans from mundane tasks (cf. driving and autonomous vehicles), from the risk of operating in unknown or perilous environments (cf. rescue scenarios), or to support timely decision-making in complex settings (cf. data-centre operations). Beyond the results that individual autonomous agents can carry out, a further opportunity lies in the collaboration of multiple agents or robots. Emerging macro-paradigms provide an approach to programming whole collectives towards global goals. Aggregate computing is one such paradigm, formally grounded in a calculus of computational fields enabling functional composition of collective behaviours that could be proved, under certain technical conditions, to be self-stabilising. In this work, we address the concept of collective autonomy, i.e., the form of autonomy that applies at the level of a group of individuals. As a contribution, we define an agent control architecture for aggregate multi-agent systems, discuss how the aggregate computing framework relates to both individual and collective autonomy, and show how it can be used to program collective autonomous behaviour. We exemplify the concepts through a simulated case study, and outline a research roadmap towards reliable aggregate autonomy. Full article
(This article belongs to the Special Issue Agents and Robots for Reliable Engineered Autonomy)
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Article
Toward Campus Mail Delivery Using BDI
J. Sens. Actuator Netw. 2020, 9(4), 56; https://doi.org/10.3390/jsan9040056 - 08 Dec 2020
Cited by 5 | Viewed by 953
Abstract
Autonomous systems developed with the Belief-Desire-Intention (BDI) architecture tend to be mostly implemented in simulated environments. In this project we sought to build a BDI agent for use in the real world for campus mail delivery in the tunnel system at Carleton University. [...] Read more.
Autonomous systems developed with the Belief-Desire-Intention (BDI) architecture tend to be mostly implemented in simulated environments. In this project we sought to build a BDI agent for use in the real world for campus mail delivery in the tunnel system at Carleton University. Ideally, the robot should receive a delivery order via a mobile application, pick up the mail at a station, navigate the tunnels to the destination station, and notify the recipient. In this paper, we discuss how we linked the Robot Operating System (ROS) with a BDI reasoning system to achieve a subset of the required use casesand demonstrated the system performance in an analogue environment. ROS handles the connections to the low-level sensors and actuators, while the BDI reasoning system handles the high-level reasoning and decision making. Sensory data is sent to the reasoning system as perceptions using ROS. These perceptions are then deliberated upon, and an action string is sent back to ROS for interpretation and driving of the necessary actuator for the action to be performed. In this paper we present our current implementation, which closes the loop on the hardware-software integration and implements a subset of the use cases required for the full system. We demonstrated the performance of the system in an analogue environment. Full article
(This article belongs to the Special Issue Agents and Robots for Reliable Engineered Autonomy)
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Perspective
Agents and Robots for Reliable Engineered Autonomy:A Perspective from the Organisers of AREA 2020
J. Sens. Actuator Netw. 2021, 10(2), 33; https://doi.org/10.3390/jsan10020033 - 14 May 2021
Cited by 1 | Viewed by 401
Abstract
Multi-agent systems, robotics and software engineering are large and active research areas with many applications in academia and industry. The First Workshop on Agents and Robots for reliable Engineered Autonomy (AREA), organised the first time in 2020, aims at encouraging cross-disciplinary collaborations and [...] Read more.
Multi-agent systems, robotics and software engineering are large and active research areas with many applications in academia and industry. The First Workshop on Agents and Robots for reliable Engineered Autonomy (AREA), organised the first time in 2020, aims at encouraging cross-disciplinary collaborations and exchange of ideas among researchers working in these research areas. This paper presents a perspective of the organisers that aims at highlighting the latest research trends, future directions, challenges, and open problems. It also includes feedback from the discussions held during the AREA workshop. The goal of this perspective is to provide a high-level view of current research trends for researchers that aim at working in the intersection of these research areas. Full article
(This article belongs to the Special Issue Agents and Robots for Reliable Engineered Autonomy)
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