Process automation is part of the knowledge base of many senior technicians and engineers. It is a learning process that follows a specific path in order to meet the defined objectives by complying with the standards, especially the safety of the installations. The PLC3000 solution aims at facilitating the teaching of PLCs for teachers, but also for students. PLC3000 has been developed with an agile pedagogical approach focused on students' learning. This tool can be easily integrated into any existing teaching, while guaranteeing an increased simplicity of use since it is accessible via a website. PLC3000 is a powerful tool offering the possibility to code in three languages defined in the standard IEC 61131–3, and to visualise the codes on a large number of interactive virtual models. This solution has been integrated in the programme of two engineering schools in France in 2022; IMT Nord Europe and ENIT. The feedback from students and its analysis are presented.

Acquiring vast and reliable data of physicochemical parameters is critical to environment monitoring. In the context of water quality analysis, data collection solutions have to overcome challenges related to the scale of environments to be explored. Sites to monitor can be large or remote. These challenges can be approached by the use of Unmanned Vehicles (UVs). Robots provide both flexibility on intervention plans and technological methods for real-time data acquisition. Being autonomous, UVs can explore areas difficult to access or far from the shore. This paper presents a nonlinear Model Predictive Control (MPC) for UV-based exploration. The strategy aims to improve the data collection of physicochemical parameters with the use of an Unmanned Surface Vehicle (USV) targeting water quality analysis. We have performed simulations based on real field experiments with a SPYBOAT® on the Heron Lake in Villeneuve d’Ascq, France. Numerical results suggest that the proposed strategy outperforms the schedule of mission planning and exploration for large areas.

Performance benchmarking has become an important topic within robotics. It is indeed, a critical way to compare different solutions under different conditions. In this paper, we focus on performance benchmarking of multi-robot systems which explore and map unknown terrains. We present a collection of metrics to objectively compare different algorithms that can be applied to collaborative multi-robot exploration. We also identify parameters that impact robotic fleet performances. By varying the parameters, we can identify strengths and limits of an algorithm. This work is also a first concrete step to address the general problem of objectively comparing different multi-robot coordination algorithms. We illustrate these contributions with realistic simulations of the frontier-based exploration strategy. The simulations were implemented in ROS, which enables to uncouple the control software from the drivers of the robot body. We can therefore use the same code on both simulation and real robots.

Mobile autonomous robots are progressively entering the mass market. Thus, manufacturers have to perform quality assurance tests on series of robots. Therefore, tests should be repeatable and as much automated as possible. Tests are also performed for purpose of repairing robots. This calls for reusing tests already defined for quality assurance. In this paper we introduce a methodology to support the definition of repeatable, reusable, semi-automated tests. Our methodology describes the process of conducting tests in a way that maximizes safety for human operators, while avoiding to damage tested robots.

Maintaining the network connectivity in mobile Multi-Robot Systems (MRSs) is a key issue in many robotic applications. In our view, the solution to this problem consists of two main steps: (i) making robots aware of the network connectivity; and (ii), making use of this knowledge to plan robots tasks without compromising connectivity. In this paper, we view the ad-hoc network connectivity as an abstraction that is independent from application issues. We propose a new distributed algorithm executing on individual robots to build the connectivity-awareness. The correctness and theoretical analysis of the proposed algorithm are given. We also show how our solution allows checking network bi-connectivity more efficiently than existing work and can be used, for example, during distributed control motion.

Exploration of an unknown environment is one of the major applications of multi-robot systems. Many works have proposed multi-robot coordination algorithms to accomplish exploration missions based on multi-agent techniques. Some of these works focus on multi-robot exploration under communication constraints. In this paper, we propose an original way to formalize and solve this issue. Our proposal relies on distributed constraint satisfaction problems (disCSP) which are an extension of classical constraint satisfaction problems (CSP). Compared to other works, our proposal is fully distributed and guaranties the exploration of an unknown environment with maintenance of connectivity between all the members of a robots' team.

In a system where classes are treated as first class objects, classes are defined as instances of other classes called metaclasses. An important benefit of using metaclasses is the ability to assign properties to classes (e.g. being abstract, being final, tracing particular messages, supporting multiple inheritance), independently from the base-level code. However, when both inheritance and instantiation are explicitly and simultaneously involved, communication between classes and their instances raises the metaclass compatibility issue. Some languages (such as SMALLTALK) address this issue but do not easily allow the assignment of specific properties to classes. In contrast, other languages (such as CLOS) allow the assignment of specific properties to classes but do not tackle the compatibility issue well.In this paper, we describe a new model of metalevel organization, called the compatibility model, which overcomes this difficulty. It allows safe metaclass programming since it makes it possible to assign specific properties to classes while ensuring metaclass compatibility. Therefore, we can take advantage of the expressive power of metaclasses to build reliable software. We extend this compatibility model in order to enable safe reuse and composition of class specific properties. This extension is implemented in NEOCLASSTALK, a fully reflective SMALLTALK.