Agricultural multi-robot systems (MRSs) are expected to provide effective solutions to improve task efficiency over large fields. However, MRSs for agricultural applications are still being investigated and several challenges need to be faced, including localization, control, path planning and navigation. This paper presents an algorithm for the control of a multi-robot system operating in row crop fields. The proposed strategy enables a multi-robot system to follow each field row in a fully distributed way, while avoiding collision. The only assumption is that each robot can estimate the relative pose with respect to the row and the preceding robot. The theoretical demonstration of the stability of the control law is given. Moreover, numerical simulations corroborate the results.

The widespread availability of network resources and the development of new generation devices allowed the industry to pass into the so-called Industry 4.0 era. In this fourth industrial revolution, Internet of Things (IoT) and robotic systems closely cooperate, reshaping their relations. This way of integration of robotic agents and IoT leads to the concept of Internet of Robotic Things (IoRT). Such disruptive technology opens new possibilities also in research fields other than manufacturing, such as agriculture, health, surveillance, and education. This paper reviews the key technologies of Industry 4.0 and the way they are implemented in IoRT architectures. In addition, it sheds light on the impact of the IoRT on other research fields, focusing on the main open challenges of the integration of robotic technologies into smart spaces.

In this paper we consider the cooperative control of the manipulation of a load on a plane by a team of mobile robots. We propose two different novel solutions. The first is a controller which ensures exact tracking of the load twist. This controller is partially decentralized since, locally, it does not rely on the state of all the robots but needs only to know the system parameters and load twist. Then we propose a fully decentralized controller that differs from the first one for the use of i) a decentralized estimation of the parameters and twist of the load based only on local measurements of the velocity of the contact points and ii) a discontinuous robustification term in the control law. The second controller ensures a practical stabilization of the twist in presence of estimation errors. The theoretical results are finally corroborated with a simulation campaign evaluating different manipulation settings.

In this paper, a distributed approach for the estimation of kinematic and inertial parameters of an unknown rigid body is presented. The body is manipulated by a pool of ground mobile manipulators. Each robot retrieves a noisy measurement of its velocity and the contact forces applied to the body. Kinematics and dynamics arguments are used to distributively estimate the relative positions of the contact points. Subsequently, distributed estimation filters and nonlinear observers are used to estimate the body mass, the relative position between its geometric center and its center of mass, and its moment of inertia. The manipulation strategy is functional to the estimation process, and is suitably designed to satisfy nonlinear observability conditions that are necessary for the success of the estimation. Numerical results corroborate our theoretical findings.

Distributed networks of sensors have been recognized to be a powerful tool for developing fully automated systems that monitor environments and human activities. Nevertheless, problems such as active control of heterogeneous sensors for high-level scene interpretation and mission execution are open. This paper presents the authors' ongoing research about design and implementation of a distributed heterogeneous sensor network that includes static cameras and multi-sensor mobile robots. The system is intended to provide robot-assisted monitoring and surveillance of large environments. The proposed solution exploits a distributed control architecture to enable the network to autonomously accomplish general-purpose and complex monitoring tasks. The nodes can both act with some degree of autonomy and cooperate with each other. The paper describes the concepts underlying the designed system architecture and presents the results obtained working on its components, including some simulations performed in a realistic scenario to validate the distributed target tracking algorithm.