Distributed Control of a Limited Angular Field-of-View Multi-Robot System in Communication-Denied Scenarios: A Probabilistic Approach

Multi-robot systems are gaining popularity over single-agent systems for their advantages. Although they have been studied in agriculture, search and rescue, surveillance, and environmental exploration, real-world implementation is limited due to agent coordination complexities caused by communication and sensor limitations. In this work, we propose a probabilistic approach to allow coordination among robots in communication-denied scenarios, where agents can only rely on visual information from a camera with a limited angular field-of-view. Our solution utilizes a particle filter to analyze uncertainty in the location of neighbors, together with Control Barrier Functions to address the exploration-exploitation dilemma that arises when robots must balance the mission goal with seeking information on undetected neighbors. This technique was tested with virtual robots required to complete a coverage mission, analyzing how the number of deployed robots affects performances and making a comparison with the ideal case of isotropic sensors and communication. Despite an increase in the amount of time required to fulfill the task, results have shown to be comparable to the ideal scenario in terms of final configuration achieved by the system

Communication Through Motion: Legibility of Multi-Robot Systems

The interaction between a user and a multi-robot system in a shared environment is a relatively uncharted topic. But, as these types of systems will increase in the future years, an efficient way of communication is necessary. To this aim, it is interesting to discover if a multi-robot system can communicate its intentions exploiting only some motion-variables, which are characteristics of the motion of the robots. This study is about the legibility of a multi-robot system: In particular, we focus on the influence of these motion-variables on the legibility of more than one group of robots that move in a shared environment with the user. These motion-variables are: Trajectory, dispersion and stiffness. They are generally used to define the motion of a group of mobile robots. Trajectory and dispersion were found relevant for the correctness of the communication between the user and the multi-robot system, while stiffness was found relevant for the rapidity of communication. The analysis of the influence of the motion-variables was carried out with an ANOVA (analysis of variance) based on a series of data coming from an experimental campaign conducted in a virtual reality set-up

On Coverage Control for Limited Range Multi-Robot Systems

This paper presents a coverage based control algorithm to coordinate a group of autonomous robots. Most of the solutions presented in the literature rely on an exact Voronoi partitioning, whose computation requires complete knowledge of the environment to be covered. This can be achieved only by robots with unlimited sensing capabilities, or through communication among robots in a limited sensing scenario. To overcome these limitations, we present a distributed control strategy to cover an unknown environment with a group of robots with limited sensing capabilities and in the absence of reliable communication. The control law is based on a limited Voronoi partitioning of the sensing area, and we demonstrate that the group of robots can optimally cover the environment using only information that is locally detected (without communication). The proposed method is validated by means of simulations and experiments carried out on a group of mobile robots

An approach based on VR to design industrial human-robot collaborative workstations

This paper presents an integrated approach for the design of human-robot collaborative workstations in industrial shop floors. In particular, the paper presents how to use virtual reality (VR) technologies to support designers in the creation of interactive workstation prototypes and in early validation of design outcomes. VR allows designers to consider and evaluate in advance the overall user experience, adopting a user-centered perspective. The proposed approach relies on two levels: the first allows designers to have an automatic generation and organization of the workstation physical layout in VR, starting from a conceptual description of its functionalities and required tools; the second aims at supporting designers during the design of human-machine interfaces (HMIs) by interaction mapping, HMI prototyping and testing in VR. The proposed approach has been applied on two realistic industrial case studies related to the design of an intensive warehouse and a collaborative assembly workstation for automotive industry, respectively. The two case studies demonstrate how the approach is suited for early prototyping of complex environments and human-machine interactions by taking into account the user experience from the early phases of design

Task-Oriented Contact Optimization for Pushing Manipulation with Mobile Robots

This work addresses the problem of transporting an object along a desired planar trajectory by pushing with mobile robots. More specifically, we concentrate on establishing optimal contacts between the object and the robots to execute the given task with minimum effort. We present a task-oriented contact placement optimization strategy for object pushing that allows calculating optimal contact points minimizing the amplitude of forces required to execute the task. Exploiting the optimized contact configuration, a motion controller uses the computed contact forces in feed-forward and position error feedback terms to realize the desired trajectory tracking task. Simulations and real experiments results confirm the validity of our approach

Hierarchical Traffic Management of Multi-AGV Systems With Deadlock Prevention Applied to Industrial Environments

This paper concerns the coordination and the traffic management of a group of Automated Guided Vehicles (AGVs) moving in a real industrial scenario, such as an automated factory or warehouse. The proposed methodology is based on a three-layer control architecture, which is described as follows: 1) the Top Layer (or Topological Layer) allows to model the traffic of vehicles among the different areas of the environment; 2) the Middle Layer allows the path planner to compute a traffic sensitive path for each vehicle; 3) the Bottom Layer (or Roadmap Layer) defines the final routes to be followed by each vehicle and coordinates the AGVs over time. In the paper we describe the coordination strategy we propose, which is executed once the routes are computed and has the aim to prevent congestions, collisions and deadlocks. The coordination algorithm exploits a novel deadlock prevention approach based on time-expanded graphs. Moreover, the presented control architecture aims at grounding theoretical methods to an industrial application by facing the typical practical issues such as graphs difficulties (load/unload locations, weak connections,), a predefined roadmap (constrained by the plant layout), vehicles errors, dynamical obstacles, etc. In this paper we propose a flexible and robust methodology for multi-AGVs traffic-aware management. Moreover, we propose a coordination algorithm, which does not rely on ad hoc assumptions or rules, to prevent collisions and deadlocks and to deal with delays or vehicle motion errors. Note to Practitioners-This paper concerns the coordination and the traffic management of a group of Automated Guided Vehicles (AGVs) moving in a real industrial scenario, such as an automated factory or warehouse. The proposed methodology is based on a three-layer control architecture, which is described as follows: 1) the Top Layer (or Topological Layer) allows to model the traffic of vehicles among the different areas of the environment; 2) the Middle Layer allows the path planner to compute a traffic sensitive path for each vehicle; 3) the Bottom Layer (or Roadmap Layer) defines the final routes to be followed by each vehicle and coordinates the AGVs over time. In the paper we describe the coordination strategy we propose, which is executed once the routes are computed and has the aim to prevent congestions, collisions and deadlocks. The coordination algorithm exploits a novel deadlock prevention approach based on time-expanded graphs. Moreover, the presented control architecture aims at grounding theoretical methods to an industrial application by facing the typical practical issues such as graphs difficulties (load/unload locations, weak connections, ), a predefined roadmap (constrained by the plant layout), vehicles errors, dynamical obstacles, etc. In this paper we propose a flexible and robust methodology for multi-AGVs traffic-aware management. Moreover, we propose a coordination algorithm, which does not rely on ad hoc assumptions or rules, to prevent collisions and deadlocks and to deal with delays or vehicle motion errors

Effect of Stubborn Agents on Bounded Confidence Opinion Dynamic Systems: Unanimity in Presence of Stubborn Agents

In this paper, various bounded confidence opinion dynamic algorithms are examined to illustrate the effect of a stubborn minority groups on opinion dynamics. A notion of variable opinion stubborn agent is defined and it is shown that stubborn minorities are able to fully control the opinions of a Hegselmann-Krause opinion dynamic system through deliberate slow variation in the opinions of stubborn agents. Furthermore, an upper bound for the change rate of stubborn agents to preserve connectivity and control other flexible agents is given. Moreover, a method based on population and growing confidence bound is presented to achieve both unanimity and stubborn opinion rejection. To support the proposed method simulation results are provided

Features and prognostic impact of distant metastases in 45 dogs with de novo stage IV cutaneous mast cell tumours: A prospective study

BACKGROUND: Distant metastases in dogs with cutaneous mast cell tumors (cMCT) are rare and incurable. The aims of this prospective study were to clarify the clinico-pathological features of stage IV cMCTs and to identify possible prognostic factors for progression-free interval (PFI) and survival time (ST). MATERIAL AND METHODS: Dogs were eligible for recruitment if they had a previously untreated, histologically confirmed cMCT and if they underwent complete staging demonstrating stage IV disease. Dogs were uniformly followed-up, whereas treatment was not standardized and included no therapy, surgery, radiation therapy, chemotherapy, tyrosine-kinase inhibitors or a combination of these. RESULTS: 45 dogs with stage IV cMCT were enrolled. All dogs had distant metastatic disease, and 41 (91.1%) dogs had also metastasis in the regional lymph node. Histopathological grade and mutational status greatly varied among dogs. Median ST was 110 days. Notably, PFI and ST were independent of well-known prognostic factors, including anatomic site, histological grade, and mutational status. Conversely, tumor diameter >3\u2009cm, more than 2 metastatic sites, bone marrow infiltration, and lack of tumor control at the primary site were confirmed to be negative prognostic factors by multivariate analysis. CONCLUSION: Currently, there is no satisfactory treatment for stage IV cMCT. Asymptomatic dogs with tumor diameter <3\u2009cm and a low tumor burden, without bone marrow infiltration may be candidates for multimodal treatment. Stage IV dogs without lymph node metastasis may enjoy a surprisingly prolonged survival. The achievement of local tumor control seems to predict a better outcome in dogs with stage IV cMCT