A two teraflop swarm

© 2018 Jones, Studley, Hauert and Winfield. We introduce the Xpuck swarm, a research platform with an aggregate raw processing power in excess of two teraflops. The swarm uses 16 e-puck robots augmented with custom hardware that uses the substantial CPU and GPU processing power available from modern mobile system-on-chip devices. The augmented robots, called Xpucks, have at least an order of magnitude greater performance than previous swarm robotics platforms. The platform enables new experiments that require high individual robot computation and multiple robots. Uses include online evolution or learning of swarm controllers, simulation for answering what-if questions about possible actions, distributed super-computing for mobile platforms, and real-world applications of swarm robotics that requires image processing, or SLAM. The teraflop swarm could also be used to explore swarming in nature by providing platforms with similar computational power as simple insects. We demonstrate the computational capability of the swarm by implementing a fast physics-based robot simulator and using this within a distributed island model evolutionary system, all hosted on the Xpucks

Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform

In this paper, we provide details of implementing a system for managing a fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse premise. While the robots are themselves autonomous in its motion and obstacle avoidance capability, the target destination for each robot is provided by a global planner. The global planner and the ground vehicles (robots) constitute a multi agent system (MAS) which communicate with each other over a wireless network. Three different approaches are explored for implementation. The first two approaches make use of the distributed computing based Networked Robotics architecture and communication framework of Robot Operating System (ROS) itself while the third approach uses Rapyuta Cloud Robotics framework for this implementation. The comparative performance of these approaches are analyzed through simulation as well as real world experiment with actual robots. These analyses provide an in-depth understanding of the inner working of the Cloud Robotics Platform in contrast to the usual ROS framework. The insight gained through this exercise will be valuable for students as well as practicing engineers interested in implementing similar systems else where. In the process, we also identify few critical limitations of the current Rapyuta platform and provide suggestions to overcome them.Comment: 14 pages, 15 figures, journal pape

Encoderless position estimation and error correction techniques for miniature mobile robots

This paper presents an encoderless position estimation technique for miniature-sized mobile robots. Odometry techniques, which are based on the hardware components, are commonly used for calculating the geometric location of mobile robots. Therefore, the robot must be equipped with an appropriate sensor to measure the motion. However, due to the hardware limitations of some robots, employing extra hardware is impossible. On the other hand, in swarm robotic research, which uses a large number of mobile robots, equipping the robots with motion sensors might be costly. In this study, the trajectory of the robot is divided into several small displacements over short spans of time. Therefore, the position of the robot is calculated within a short period, using the speed equations of the robot's wheel. In addition, an error correction function is proposed that estimates the errors of the motion using a current monitoring technique. The experiments illustrate the feasibility of the proposed position estimation and error correction techniques to be used in miniature-sized mobile robots without requiring an additional sensor

Towards a cloud‑based automated surveillance system using wireless technologies

Cloud Computing can bring multiple benefits for Smart Cities. It permits the easy creation of centralized knowledge bases, thus straightforwardly enabling that multiple embedded systems (such as sensor or control devices) can have a collaborative, shared intelligence. In addition to this, thanks to its vast computing power, complex tasks can be done over low-spec devices just by offloading computation to the cloud, with the additional advantage of saving energy. In this work, cloud’s capabilities are exploited to implement and test a cloud-based surveillance system. Using a shared, 3D symbolic world model, different devices have a complete knowledge of all the elements, people and intruders in a certain open area or inside a building. The implementation of a volumetric, 3D, object-oriented, cloud-based world model (including semantic information) is novel as far as we know. Very simple devices (orange Pi) can send RGBD streams (using kinect cameras) to the cloud, where all the processing is distributed and done thanks to its inherent scalability. A proof-of-concept experiment is done in this paper in a testing lab with multiple cameras connected to the cloud with 802.11ac wireless technology. Our results show that this kind of surveillance system is possible currently, and that trends indicate that it can be improved at a short term to produce high performance vigilance system using low-speed devices. In addition, this proof-of-concept claims that many interesting opportunities and challenges arise, for example, when mobile watch robots and fixed cameras would act as a team for carrying out complex collaborative surveillance strategies.Ministerio de Economía y Competitividad TEC2016-77785-PJunta de Andalucía P12-TIC-130

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Development of personal area network (PAN) for mobile robot using bluetooth transceiver

The work presents the concept of providing a Personal Area Network (PAN) for microcontroller based mobile robots using Bluetooth transceiver. With the concept of replacing cable, low cost, low power consumption and communication range between 10m to 100m, Bluetooth is suitable for communication between mobile robots since most mobile robots are powered by batteries and have high mobility. The network aimed to support real-time control of up to two mobile robots from a master mobile robot through communication using Bluetooth transceiver. If a fast network radio link is implemented, a whole new world of possibilities is opened in the research of robotics control and Artificial Intelligence (AI) research works, sending real time image and information. Robots could communicate through obstacles or even through walls. Bluetooth Ad Hoc topology provides a simple communication between devices in close by forming PAN. A system contained of both hardware and software is designed to enable the robots to form a PAN and communicating, sharing information. Three microcontroller based mobile robots are built for this research work. Bluetooth Protocol Stack and mobile robot control architecture is implemented on a single microcontroller chip. The PAN enabled a few mobile robots to communicate with each other to complete a given task. The wireless communication between mobile robots is reliable based from the result of experiments carried out. Thus this is a platform for multi mobile robots system and Ad Hoc networking system. Results from experiments show that microcontroller based mobile robots can easily form a Bluetooth PAN and communicate with each other