This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. These algorithms are generally meant to control collectives of hundreds or even thousands of robots; however, for reasons of cost, time, or complexity, they are generally validated in simulation only, or on a group of a few tens of robots. To address this issue, this paper presents Kilobot, a low-cost robot designed to make testing collective algorithms on hundreds or thousands of robots accessible to robotics researchers. To enable the possibility of large Kilobot collectives where the number of robots is an order of magnitude larger than the largest that exist today, each robot is made with only $14 worth of parts and takes 5 minutes to assemble. Furthermore, the robot design allows a single user to easily operate a large Kilobot collective, such as programming, powering on, and charging all robots, which would be difficult or impossible to do with many existing robotic systems.

/pdf/kilobot-a-low-cost-scalable-robot-system-for-collective-1pjo9kvxw8.pdf

Kilobot: A low cost scalable robot system for collective behaviors

A fundamental problem that the bearing rigidity theory studies is to determine when a framework can be uniquely determined up to a translation and a scaling factor by its inter-neighbor bearings While many previous works focused on the bearing rigidity of two-dimensional frameworks, a first contribution of this paper is to extend these results to arbitrary dimensions It is shown that a framework in an arbitrary dimension can be uniquely determined up to a translation and a scaling factor by the bearings if and only if the framework is infinitesimally bearing rigid In this paper, the proposed bearing rigidity theory is further applied to the bearing-only formation stabilization problem where the target formation is defined by inter-neighbor bearings and the feedback control uses only bearing measurements Nonlinear distributed bearing-only formation control laws are proposed for the cases with and without a global orientation It is proved that the control laws can almost globally stabilize infinitesimally bearing rigid formations Numerical simulations are provided to support the analysis

/pdf/bearing-rigidity-and-almost-global-bearing-only-formation-2nkkfr4vub.pdf

Bearing Rigidity and Almost Global Bearing-Only Formation Stabilization

Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

https://www.mdpi.com/1424-8220/15/12/29845/pdf

Theory and Application of Magnetic Flux Leakage Pipeline Detection

In swarm robotics multiple robots collectively solve problems by forming advantageous structures and behaviors similar to the ones observed in natural systems, such as swarms of bees, birds, or fish. However, the step to industrial applications has not yet been made successfully. Literature is light on real-world swarm applications that apply actual swarm algorithms. Typically, only parts of swarm algorithms are used which we refer to as basic swarm behaviors. In this paper we collect and categorize these behaviors into spatial organization, navigation, decision making, and miscellaneous. This taxonomy is then applied to categorize a number of existing swarm robotic applications from research and industrial domains. Along with the classification, we give a comprehensive overview of research platforms that can be used for testing and evaluating swarm behavior, systems that are already on the market, and projects that target a specific market. Results from this survey show that swarm robotic applications are still rare today. Many industrial projects still rely on centralized control, and even though a solution with multiple robots is employed, the principal idea of swarm robotics of distributed decision making is neglected. We identified mainly following reasons: First of all, swarm behavior emerging from local interactions is hard to predict and a proof of its eligibility for applications in an industrial context is difficult to provide. Second, current communication architectures often do not match requirements for swarm communication, which often leads to a system with a centralized communication infrastructure. Finally, testing swarms for real industrial applications is an issue, since deployment in a productive environment is typically too risky and simulations of a target system may not be sufficiently accurate. In contrast, the research platforms present a means for transforming swarm robotics solutions from theory to prototype industrial systems.

Swarm Robotic Behaviors and Current Applications

This paper describes the experiences of using an advanced, low-cost robot in science, technology, engineering, and mathematics (STEM) education. It presents three innovations: It is a powerful, cheap, robust, and small advanced personal robot; it forms the foundation of a problem-based learning curriculum; and it enables a novel multi-robot curriculum while fostering collaborative team work on assignments. The robot design has many features specific to educators: It is advanced enough for academic research, has a broad feature set to support a wide range of curricula, and is inexpensive enough to be an effective outreach tool. The low cost allows each student to have their own robot for the semester, so they can work on activities outside the classroom. This robot was used in three different classes in which it was the foundation for an innovative problem-based learning curriculum. In particular, the robot has specialized sensors and a communications system that supports novel multi-robot curricula, which encourage student interaction in new ways. The results are promising; the robot was a big success in graduate, undergraduate, and outreach activities. Finally, student assessments indicate a greater interest and understanding of engineering and other STEM majors, and class evaluations were consistently above average.

Using Multi-Robot Systems for Engineering Education: Teaching and Outreach With Large Numbers of an Advanced, Low-Cost Robot

We describe a new low-cost robot design that enables large-scale multirobot research, innovative new curriculum, and multi-robotics outreach to younger students There are four main parts to the system: the r-one robot, a Python development environment, a camera tracking system for ground-truth localization, and server software to connect all the pieces together This paper presents our preliminary work on the robot design and our experience using it to teach an introductory engineering class The hardware can support classes in computer science, electrical engineering, and mechanical engineering The low-cost and small size will enable more research groups to perform multi-robot experiments on physical hardware The Python development environment greatly simplifies programming and will make robotics more accessible to a larger group of educators, students, and researchers

A Low-Cost Multi-robot System for Research, Teaching, and Outreach

We propose scale-free coordinates as an alternative coordinate system for multi-robot systems with large robot populations. Scale-free coordinates allow each robot to know, up to scaling, the relative position and orientation of other robots in the network. We consider a weak sensing model where each robot is only capable of measuring the angle, relative to its own heading, to each of its neighbors. Our contributions are three-fold. First, we derive a precise mathematical characterization of the computability of scale-free coordinates using only bearing measurements, and we describe an efficient algorithm to obtain them. Second, through simulations we show that even in graphs with low average vertex degree, most robots are able to compute the scale-free coordinates of their neighbors using only two-hop bearing measurements. Finally, we present an algorithm to compute scale-free coordinates that is tailored to low-cost systems with limited communication bandwidth and sensor resolution. Our algorithm mitigates the impact of sensing errors through a simple yet effective noise sensitivity model. We validate our implementation with real-world robot experiments using static accuracy measurements and a simple scale-free motion controller.

Scale-free coordinates for multi-robot systems with bearing-only sensors

Scale-Free Coordinates for Multi-robot Systems with Bearing-Only Sensors.

We describe a proof-of-concept design for a low-cost two-degree-of-freedom robotic arm that incorporates series elastic actuators (SEAs) with force sensing. The cost effectiveness of the design will enable the construction of compliant manipulators for multi-robot systems with large populations. The arm assembly attaches to a commercially available mobile robot chassis to perform multi-robot coordination. In this work, we present the design of a robot arm and data from experiments to characterize the accuracy and resolution of the force sensing. We describe a force-following manipulation experiment using two robots. The experiment measures strain on a rigid bar between two robots. The data shows the feasibility of using SEAs for force sensing to reduce the strain in the bar. This is the first step towards a distributed force controller for multi-robot object coordination with large numbers of robots.

Andrew J. Lynch

Papers

Using Multi-Robot Systems for Engineering Education: Teaching and Outreach With Large Numbers of an Advanced, Low-Cost Robot

A Low-Cost Multi-robot System for Research, Teaching, and Outreach

Scale-free coordinates for multi-robot systems with bearing-only sensors

Scale-Free Coordinates for Multi-robot Systems with Bearing-Only Sensors.

Design of a low-cost series elastic actuator for multi-robot manipulation