A Parallel Distributed Strategy for Arraying a Scattered Robot Swarm

We consider the problem of organizing a scattered group of $n$ robots in two-dimensional space, with geometric maximum distance $D$ between robots. The communication graph of the swarm is connected, but there is no central authority for organizing it. We want to arrange them into a sorted and equally-spaced array between the robots with lowest and highest label, while maintaining a connected communication network. In this paper, we describe a distributed method to accomplish these goals, without using central control, while also keeping time, travel distance and communication cost at a minimum. We proceed in a number of stages (leader election, initial path construction, subtree contraction, geometric straightening, and distributed sorting), none of which requires a central authority, but still accomplishes best possible parallelization. The overall arraying is performed in $O(n)$ time, $O(n^2)$ individual messages, and $O(nD)$ travel distance. Implementation of the sorting and navigation use communication messages of fixed size, and are a practical solution for large populations of low-cost robots

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

Priority-Based Distributed Coordination for Heterogeneous Multi-Robot Systems with Realistic Assumptions

A standing challenge in current intralogistics is to reliably, effectively, yet safely coordinate large-scale, heterogeneous multi-robot fleets without posing constraints on the infrastructure or unrealistic assumptions on robots. A centralized approach, proposed by some of the authors in prior work, allows to overcome these limitations with medium-scale fleets (i.e., tens of robots). With the aim of scaling to hundreds of robots, in this article we explore a decentralized variant of the same approach. The proposed framework maintains the key features of the original approach, namely, ensuring safety despite uncertainties on robot motions, and generality with respect to robot platforms, motion planners and controllers. We include considerations on liveness and report solutions to prevent or recover from deadlocks in specific situations. We validate the approach empirically in simulation with large, heterogeneous multi-robot fleets (with up to 100 robots) operating in both benchmark and realistic environments

Multi-Robot Systems: Challenges, Trends and Applications

This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics

Coordination of Multirobot Systems Under Temporal Constraints

Multirobot systems have great potential to change our lives by increasing efficiency or decreasing costs in many applications, ranging from warehouse logistics to construction. They can also replace humans in dangerous scenarios, for example in a nuclear disaster cleanup mission. However, teleoperating robots in these scenarios would severely limit their capabilities due to communication and reaction delays. Furthermore, ensuring that the overall behavior of the system is safe and correct for a large number of robots is challenging without a principled solution approach. Ideally, multirobot systems should be able to plan and execute autonomously. Moreover, these systems should be robust to certain external factors, such as failing robots and synchronization errors and be able to scale to large numbers, as the effectiveness of particular tasks might depend directly on these criteria. This thesis introduces methods to achieve safe and correct autonomous behavior for multirobot systems. Firstly, we introduce a novel logic family, called counting logics, to describe the high-level behavior of multirobot systems. Counting logics capture constraints that arise naturally in many applications where the identity of the robot is not important for the task to be completed. We further introduce a notion of robust satisfaction to analyze the effects of synchronization errors on the overall behavior and provide complexity analysis for a fragment of this logic. Secondly, we propose an optimization-based algorithm to generate a collection of robot paths to satisfy the specifications given in counting logics. We assume that the robots are perfectly synchronized and use a mixed-integer linear programming formulation to take advantage of the recent advances in this field. We show that this approach is complete under the perfect synchronization assumption. Furthermore, we propose alternative encodings that render more efficient solutions under certain conditions. We also provide numerical results that showcase the scalability of our approach, showing that it scales to hundreds of robots. Thirdly, we relax the perfect synchronization assumption and show how to generate paths that are robust to bounded synchronization errors, without requiring run-time communication. However, the complexity of such an approach is shown to depend on the error bound, which might be limiting. To overcome this issue, we propose a hierarchical method whose complexity does not depend on this bound. We show that, under mild conditions, solutions generated by the hierarchical method can be executed safely, even if such a bound is not known. Finally, we propose a distributed algorithm to execute multirobot paths while avoiding collisions and deadlocks that might occur due to synchronization errors. We recast this problem as a conflict resolution problem and characterize conditions under which existing solutions to the well-known drinking philosophers problem can be used to design control policies that prevents collisions and deadlocks. We further provide improvements to this naive approach to increase the amount of concurrency in the system. We demonstrate the effectiveness of our approach by comparing it to the naive approach and to the state-of-the-art.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162921/1/ysahin_1.pd