Abstract. Relative positioning systems play a vital role in current multirobot systems. We present a self-contained detection and tracking approach, where a robot estimates a distance (range) and an angle (bearing) to another robot using measurements extracted from the raw data provided by two laser range finders. We propose a method based on the detection of circular features with least-squares fitting and filtering out outliers using a map-based selection. We improve the estimate of the relative robot position and reduce its uncertainty by feeding measurements into a Kalman filter, resulting in an accurate tracking system. We evaluate the performance of the algorithm in a realistic indoor environment to demonstrate its robustness and reliability.

Abstract-Multi-robot cooperative navigation in real-world environments is essential in many applications, including surveillance and search-and-rescue missions. State-of-the-art methods for cooperative navigation are often tested in ideal laboratory conditions and not ready to be deployed in realworld environments, which are often cluttered with static and dynamic obstacles. In this work, we explore a graph-based framework to achieve control of real robot formations moving in a world cluttered with a variety of obstacles by introducing a new distributed algorithm for reconfiguring the formation shape. We systematically validate the reconfiguration algorithm using three real robots in scenarios of increasing complexity.

The work described is part of a long term program of introducing institutional robotics, a novel framework for the coordination of robot teams that stems from institutional economics concepts. Under the framework, institutions are cumulative sets of persistent artificial modifications made to the environment or to the internal mechanisms of a subset of agents, thought to be functional for the collective order. In this article we introduce a formal model of institutional controllers based on Petri nets. We define executable Petri nets-an extension of Petri nets that takes into account robot actions and sensing-to design, program, and execute institutional controllers. We use a generalized stochastic Petri net view of the robot team controlled by the institutional controllers to model and analyze the stochastic performance of the resulting distributed robotic system. The ability of our formalism to replicate results obtained using other approaches is assessed through realistic simulations of up to 40 e-puck robots. In particular, we model a robot swarm and its institutional controller with the goal of maintaining wireless connectivity, and successfully compare our model predictions and simulation results with previously reported results, obtained by using finite state automaton models and controllers.

This work is developed in the framework of Institutional Robotics (IR), an approach to cooperative distributed robotic systems that draws inspiration from the social sciences. We consider a case study concerned with a swarm of simple robots which has to maintain wireless connectivity and a certain degree of spatial compactness. Robots have local, bounded communication capabilities and have to execute the task (running an IR controller) using exclusively as information their current number of wireless connections to neighbors. For the very same case study, we previously introduced an IR-based macroscopic model for the behavior of a large number of robots, validated using a submicroscopic model implemented through a realistic simulator. In this work, we go a step further and validate our submicroscopic model with real world experiments, duplicating accurately the conditions used, including a large number of robots and noisy communication channels. The main conclusions of this paper are two-fold. First, the IR approach was able to maintain the wireless connectivity of a swarm of 40 real, resource-constrained robots. This speaks in favor of the robustness and scalability of such approach. Second, the submicroscopic model implemented is faithfully capturing the reality and can be used to further optimize the performances of distributed control strategies using an IR approach.

The way human beings engage with material things in our environment is experiencing rapid modification. Human and non-human, natural and artificial creatures are on the verge of building unprecedented relations of sociability. This paper takes this process as a horizon for Social Robotics, advancing a new approach to coordinate systems of multiple robots within social spaces durably shared by humans and machines. Given the fact that institutions are the tools in use within human societies to shape social action over long periods of time, we use human-inspired institutions to deal with scenarios involving many-to-many human-robot lasting interactions. Our approach, Institutional Robotics, is inspired by leading economists and philosophers having dedicated sustained efforts to the understanding of social institutions. This paper: (1) advocates the importance of an institution-based approach for multi-robot systems (Institutional Robotics) in real-world human-populated environments, where many-to-many social interactions among robots and humans must be considered; (2) reviews experiments conducted (including novel experimental work) and methodologies used in the process of advancing Institutional Robotics. Both contributions pave the way for a new institution-based methodology to coordinate robot collec-B Porfírio Silva tives, which stems from an inter-disciplinary approach based on robotics, social sciences and philosophy.