Towards formal models and languages for verifiable Multi-Robot Systems

Incorrect operations of a Multi-Robot System (MRS) may not only lead to unsatisfactory results, but can also cause economic losses and threats to safety. These threats may not always be apparent, since they may arise as unforeseen consequences of the interactions between elements of the system. This call for tools and techniques that can help in providing guarantees about MRSs behaviour. We think that, whenever possible, these guarantees should be backed up by formal proofs to complement traditional approaches based on testing and simulation. We believe that tailored linguistic support to specify MRSs is a major step towards this goal. In particular, reducing the gap between typical features of an MRS and the level of abstraction of the linguistic primitives would simplify both the specification of these systems and the verification of their properties. In this work, we review different agent-oriented languages and their features; we then consider a selection of case studies of interest and implement them useing the surveyed languages. We also evaluate and compare effectiveness of the proposed solution, considering, in particular, easiness of expressing non-trivial behaviour.Comment: Changed formattin

CrazyChoir: Flying Swarms of Crazyflie Quadrotors in ROS 2

This paper introduces CrazyChoir, a modular Python framework based on the Robot Operating System (ROS) 2. The toolbox provides a comprehensive set of functionalities to simulate and run experiments on teams of cooperating Crazyflie nano-quadrotors. Specifically, it allows users to perform realistic simulations over robotic simulators as, e.g., Webots and includes bindings of the firmware control and planning functions. The toolbox also provides libraries to perform radio communication with Crazyflie directly inside ROS 2 scripts. The package can be thus used to design, implement and test planning strategies and control schemes for a Crazyflie nano-quadrotor. Moreover, the modular structure of CrazyChoir allows users to easily implement online distributed optimization and control schemes over multiple quadrotors. The CrazyChoir package is validated via simulations and experiments on a swarm of Crazyflies for formation control, pickup-and-delivery vehicle routing and trajectory tracking tasks. CrazyChoir is available at https://github.com/OPT4SMART/crazychoir

Cooperative Models of Particle Swarm Optimizers

Particle Swarm Optimization (PSO) is one of the most effFective optimization tools, which emerged in the last decade. Although, the original aim was to simulate the behavior of a group of birds or a school of fish looking for food, it was quickly realized that it could be applied in optimization problems. Different directions have been taken to analyze the PSO behavior as well as improving its performance. One approach is the introduction of the concept of cooperation. This thesis focuses on studying this concept in PSO by investigating the different design decisions that influence the cooperative PSO models' performance and introducing new approaches for information exchange. Firstly, a comprehensive survey of all the cooperative PSO models proposed in the literature is compiled and a definition of what is meant by a cooperative PSO model is introduced. A taxonomy for classifying the different surveyed cooperative PSO models is given. This taxonomy classifies the cooperative models based on two different aspects: the approach the model uses for decomposing the problem search space and the method used for placing the particles into the different cooperating swarms. The taxonomy helps in gathering all the proposed models under one roof and understanding the similarities and differences between these models. Secondly, a number of parameters that control the performance of cooperative PSO models are identified. These parameters give answers to the four questions: Which information to share? When to share it? Whom to share it with? and What to do with it? A complete empirical study is conducted on one of the cooperative PSO models in order to understand how the performance changes under the influence of these parameters. Thirdly, a new heterogeneous cooperative PSO model is proposed, which is based on the exchange of probability models rather than the classical migration of particles. The model uses two swarms that combine the ideas of PSO and Estimation of Distribution Algorithms (EDAs) and is considered heterogeneous since the cooperating swarms use different approaches to sample the search space. The model is tested using different PSO models to ensure that the performance is robust against changing the underlying population topology. The experiments show that the model is able to produce better results than its components in many cases. The model also proves to be highly competitive when compared to a number of state-of-the-art cooperative PSO algorithms. Finally, two different versions of the PSO algorithm are applied in the FPGA placement problem. One version is applied entirely in the discrete domain, which is the first attempt to solve this problem in this domain using a discrete PSO (DPSO). Another version is implemented in the continuous domain. The PSO algorithms are applied to several well-known FPGA benchmark problems with increasing dimensionality. The results are compared to those obtained by the academic Versatile Place and Route (VPR) placement tool, which is based on Simulated Annealing (SA). The results show that these methods are competitive for small and medium-sized problems. For higher-sized problems, the methods provide very close results. The work also proposes the use of different cooperative PSO approaches using the two versions and their performances are compared to the single swarm performance

Adaptive scheduling based on self-organized holonic swarm of schedulers

Scheduling plays an important role in the companies’ competiveness, dealing with complex combinatorial problems subject to uncertainty and emergence. In particular, in the ramp-up phase of small lot-sizes of complex products, scheduling is more demanding, e.g. due to late requests and immature technology products and processes. This paper presents the principles of a distributed scheduling architecture based on holonic and swarm principles and implemented using multi-agent system technology. In particular, it is described the coordination among the network of the swarm of schedulers and analysed the impact of embedded self-organization mechanisms.The research leading to these results has received funding from the European Union Seventh Framework Programme FP7 ARUM project, under grant agreement n° 314056.info:eu-repo/semantics/publishedVersio

Security, privacy and safety evaluation of dynamic and static fleets of drones

Inter-connected objects, either via public or private networks are the near future of modern societies. Such inter-connected objects are referred to as Internet-of-Things (IoT) and/or Cyber-Physical Systems (CPS). One example of such a system is based on Unmanned Aerial Vehicles (UAVs). The fleet of such vehicles are prophesied to take on multiple roles involving mundane to high-sensitive, such as, prompt pizza or shopping deliveries to your homes to battlefield deployment for reconnaissance and combat missions. Drones, as we refer to UAVs in this paper, either can operate individually (solo missions) or part of a fleet (group missions), with and without constant connection with the base station. The base station acts as the command centre to manage the activities of the drones. However, an independent, localised and effective fleet control is required, potentially based on swarm intelligence, for the reasons: 1) increase in the number of drone fleets, 2) number of drones in a fleet might be multiple of tens, 3) time-criticality in making decisions by such fleets in the wild, 4) potential communication congestions/lag, and 5) in some cases working in challenging terrains that hinders or mandates-limited communication with control centre (i.e., operations spanning long period of times or military usage of such fleets in enemy territory). This self-ware, mission-focused and independent fleet of drones that potential utilises swarm intelligence for a) air-traffic and/or flight control management, b) obstacle avoidance, c) self-preservation while maintaining the mission criteria, d) collaboration with other fleets in the wild (autonomously) and e) assuring the security, privacy and safety of physical (drones itself) and virtual (data, software) assets. In this paper, we investigate the challenges faced by fleet of drones and propose a potential course of action on how to overcome them.Comment: 12 Pages, 7 Figures, Conference, The 36th IEEE/AIAA Digital Avionics Systems Conference (DASC'17

Design of an UAV swarm

This master thesis tries to give an overview on the general aspects involved in the design of an UAV swarm. UAV swarms are continuoulsy gaining popularity amongst researchers and UAV manufacturers, since they allow greater success rates in task accomplishing with reduced times. Appart from this, multiple UAVs cooperating between them opens a new field of missions that can only be carried in this way. All the topics explained within this master thesis will explain all the agents involved in the design of an UAV swarm, from the communication protocols between them, navigation and trajectory analysis and task allocation

CSR and Social Marketing: What is the desired role for Universities in fostering Public Policies?

The paper aims to identify the role of Universities in fostering public policies, through the promotion of social responsibility, and the implementation of social marketing initiatives. This innovative approach is particularly interesting since the literature does not cover, until now, the importance of adopting a social responsibility strategy within Universities, in order to foster public policies for development. First, Corporate Social Responsibility should be developed at Universities. For this purpose, an integrative approach that embraces marketing, economic, ecological, and social aspects is proposed, through the design of a strategic action plan, which includes three operational levels: analysis, implementation and assessment. Second, in order to foster the impact of public policies for development, social marketing initiatives should be implemented among institutional and social networks where Universities assume an increasing strategic role.Corporate Social Responsibility; Government Policy; Social Marketing