Bernát Wiandt

Kilogrid: a novel experimental environment for the Kilobot robot

We present the Kilogrid, an open-source virtualization environment and data logging manager for the Kilobot robot, Kilobot for short. The Kilogrid has been designed to extend the sensory-motor abilities of the Kilobot, to simplify the task of collecting data during experiments, and to provide researchers with a tool to fine-control the experimental setup and its parameters. Based on the design of the Kilobot and compatible with existing hardware, the Kilogrid is a modular system composed of a grid of computing nodes, or modules that provides a bidirectional communication channel between the Kilobots and a remote workstation. In this paper, we describe the hardware and software architecture of the Kilogrid system as well as its functioning to accompany its release as a new open hardware tool for the swarm robotics community. We demonstrate the capabilities of the Kilogrid using a 200-module Kilogrid, swarms of up to 100 Kilobots, and four different case studies: exploration and obstacle avoidance, site selection based on multiple gradients, plant watering, and pheromone-based foraging. Through this set of case studies, we show how the Kilogrid allows the experimenter to virtualize sensors and actuators not available to the Kilobot and to automatize the collection of data essential for the analysis of the experiments.

Measurements of a real-time transit feed service architecture for mobile participatory sensing

We spend a substantial part of our time with traveling, in crowded cities usually taking public transportation. It is important, making travel planning easier, to have accurate information about vehicle arrival times at the stops. Most of the public transport operators make their timetables freely available either on the web or in some special format, like GTFS (General Transit Feed Specification). However, they contain static information only, not reflecting the actual traffic conditions. Mobile participatory sensing can help extend the basic service with real-time updates letting the crowd collect the required data. With this respect we believe that such participatory sensing based application must offer a day zero service following incremental service extension. In this paper, we discuss how to realize real-time refinements to static GTFS data based on mobile participatory sensing. We show how this service can be implemented by an XMPP (Extensible Messaging and Presence Protocol) based mobile participatory sensing architecture and we evaluate its performance.

Kilogrid: A modular virtualization environment for the Kilobot robot

We introduce the Kilogrid, a modular and scalable virtualization environment aimed at swarm robotics research with the Kilobot robot. The main purpose of the Kilogrid is to complement the Kilobots by overcoming some of their limitations (i.e., limited sensors and actuators), making it easier to experiment and to collect data with large groups of robots. The Kilogrid allows researchers to study scenarios featuring a level of complexity that cannot be reached using the Kilobots alone. The Kilogrid is composed of several modules, where each module contains four cells of 50×50 mm2. The cells allow for bi-directional communication with the Kilobots. Our first version of a Kilogrid is composed of 64 cells and covers a total area of 400×400 mm2. We demonstrate the features of the Kilogrid with two case studies in which: (i) we extend the sensory system of the Kilobots, (ii) we allow the Kilobots to modify the environment, and (iii) we collect data (e.g., position, state) from the Kilobots while the experiment is running.

A Novel Spatial Property Aware Multihop Communication Solution for Autonomous Mobile Networks

In line with traditional communication systems, more and more attention is given to autonomous, self-organized networks with no central infrastructure, based on peer-to-peer communication. Designing multihop broadcast protocols for these networks is a complex problem as the task of these protocols is to disseminate messages in a network effectively while avoiding unnecessary use of resources. The vast majority of these protocols (as those used in the present day Internet) do not use spatial information of the nodes to optimize the bandwidth and channel usage. By increasing the awareness of the nodes, equipping them with their physical location, we can achieve a higher level of autonomous functioning, better performance, and higher level communication primitives, like transmitting in a given direction. We have designed a novel communication protocol, based on the spatial properties of the system, the Direction Based Handshake Gossiping, which was implemented in our self-organizing network simulator. For performance comparison we picked three other location based data dissemination protocols from the literature (Distance Adaptive Dissemination, the General Probabilistic Broadcast Algorithm, and Ni et als location-based scheme). Our simulations show that our solution overperforms the other three protocols in terms of control overhead and number of duplications, which is crucial in self-organized mobile networks, where radio band with and energy are usually scarce resources.

Self-organized graph partitioning approach for multi-agent patrolling in generic graphs

Recently multi-agent patrolling became more and more crucial in security, monitoring, etc. applications. It can be used, for example, to monitor points of interest in space, such as measurement points or entrances to a guarded area. A good patrolling strategy would ensure frequent visits to all points of interest defined by a user. A variety of centralized and distributed approaches exist already to the multi-agent patrolling problem, ranging from simple reactive solutions to sophisticated planning approaches. However there has been no self-organizing partition based solution proposed that can match and improve on the performance of already existing algorithms. In this article we introduce a self-organizing autonomous algorithm to partition a graph into non-overlapping subgraphs and assign the resulting subgraphs to agents to perform patrolling. We compare our solution to other patrolling algorithms in a thorough performance evaluation and show that our autonomous solution can outperform state of the art patrolling schemes.

Token-based autonomous task allocation in flocking systems

There are serious contributions to the theoretical foundations of flocking systems, but there are only few systems which have the capability of autonomous task allocation, however, many use cases demand this functionality. The implementation of a task allocation algorithm could be a serious challenge even in a simulated environment due to the numerous problems arising from the nature of these systems. This paper proposes a novel algorithm to find the optimal allocation of heterogeneous agents to heterogeneous tasks by utilizing distributed auctions based on local peer-to-peer wireless communication and exploiting graph theory with a tree-based multicast protocol. The solution was tested over a number of different scenarios and compared to existing algorithms in order to measure and prove its capability in handling autonomous task allocation in different systems as well.

Performance evaluation of a live, crowdsensing based transit feed service architecture

Taking public transportation is an efficient and environmentally sound way of traveling in most of the cities. Unfortunately, the static schedule information of the public transport vehicles, available at the stops, on the web or in some special format like GTFS (General Transit Feed Specification), usually does not reflect the actual traffic situation. However, realtime traffic updates require the gathering of an immense amount of tracking data. Mobile crowdsensing, via the mobile devices of the crowd, can offer a cheap and efficient way for collecting such data. Nonetheless, for motivating active participation some day zero service must be provided to the users. In this paper, we discuss how to realize a live public transport information service extending a static timetable based on GTFS data, as the day zero service, using the power of the crowd for data collection. We detail the design of such a service implemented by an XMPP (Extensible Messaging and Presence Protocol) based mobile crowdsensing architecture and evaluate its performance. We show how we can build a scalable service architecture even with commodity hardware to handle thousands of users.

Spatial Computing Meets Realistic Mobile Wireless Problems

Controlling and leveraging the vast and ever-growing number of wireless devices around us has become a serious problem. Spatial computing offers a promising approach toward solving this problem, in the form of higher-level dis-tributed programming abstractions. Many challenging mobile communications problems, however, can only be investigated using a realistic and detailed model of wireless communication. We thus demonstrate a new research platform, integrating the MIT Proto spatial computing suite with the OMNeT++ network simulator framework, which will enable investigation of spatial computing solutions to difficult mobile wireless problems.

Efficient Multihop Broadcast with Distributed Protocol Evolution

In this paper we describe an efficient way of implementing multi hop broadcast in ad hoc mobile networks with an online, distributed machine intelligence solution. In our solution not just the runtime parameters of predefined protocols are optimized, but the decision logic itself also emerges dynamically. The model is based on genetic programming and natural selection: sucessive generations of protocol instances are produced to approximate optimal performance by picking certain instances from the previous generation (natural selection) and combining them with each other and/or mutating (genetic operators) them. We implemented (i) a genetic programming language to describe protocols, and (ii) defined a distributed, communication-wise non-intensive, stigmergic feed-forward evaluation and selection mechanism over protocol instances, and (iii) a budget based fair execution model for competing protocols. The results indicate that online, autonomous protocol evolution outperforms traditional approaches, by adapting to the situation at hand, when used for the multi-hop broadcast problem in ad hoc mobile networks. The evolution also protected the system from the negative effects of initially present harmful protocols.