Quality-sensitive foraging by a robot swarm through virtual pheromone trails

Large swarms of simple autonomous robots can be employed to find objects clustered at random locations, and transport them to a central depot. This solution offers system parallelisation through concurrent environment exploration and object collection by several robots, but it also introduces the challenge of robot coordination. Inspired by ants’ foraging behaviour, we successfully tackle robot swarm coordination through indirect stigmergic communication in the form of virtual pheromone trails. We design and implement a robot swarm composed of up to 100 Kilobots using the recent technology Augmented Reality for Kilobots (ARK). Using pheromone trails, our memoryless robots rediscover object sources that have been located previously. The emerging collective dynamics show a throughput inversely proportional to the source distance. We assume environments with multiple sources, each providing objects of different qualities, and we investigate how the robot swarm balances the quality-distance trade-off by using quality-sensitive pheromone trails. To our knowledge this work represents the largest robotic experiment in stigmergic foraging, and is the first complete demonstration of ARK, showcasing the set of unique functionalities it provides

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

Platform Development for the Implementation and Testing of New Swarming Strategies

Gemstone Team SWARM-AISwarm robotics--the use of multiple autonomous robots in coordination to accomplish a task--is useful for mapping, light package transport, and search and rescue operations, among other applications. Researchers and industry professionals have developed robotic swarm mechanisms to accomplish these tasks. Some of those mechanisms or “strategies” have been tested on hardware; however, the technical requirements involved in fielding a drone swarm can be prohibitive to physical testing. Team SWARM-AI has developed a platform that provides a starting point for testing new swarming strategies. This platform allows the user to select vehicles of their choosing- either air, land, or water based, or some combination thereof- as well as define their own swarming method. Using a novel decentralized approach to ground control software, this platform provides a user interface and a system of computational “units” to coordinate drone swarms with a centralized, decentralized, or combination architecture. Additionally, the platform propagates user input from the master unit to the rest of the swarm and allows each unit to request sensor data from other units. The user is free to edit the processes by which each drone interacts with the environment and the rest of the swarm, giving them freedom to test their swarming strategy. The software system is then tested with a swarm of quadcopters using Software in the Loop (SITL) testing

Multi‑Agent Foraging: state‑of‑the‑art and research challenges

International audienceThe foraging task is one of the canonical testbeds for cooperative robotics, in which a collection of robots has to search and transport objects to specific storage point(s). In this paper, we investigate the Multi-Agent Foraging (MAF) problem from several perspectives that we analyze in depth. First, we define the Foraging Problem according to literature definitions. Then we analyze previously proposed taxonomies, and propose a new foraging taxonomy characterized by four principal axes: Environment, Collective, Strategy and Simulation, summarize related foraging works and classify them through our new foraging taxonomy. Then, we discuss the real implementation of MAF and present a comparison between some related foraging works considering important features that show extensibility, reliability and scalability of MAF systems. Finally we present and discuss recent trends in this field, emphasizing the various challenges that could enhance the existing MAF solutions and make them realistic

Cooperative Avoidance Control-based Interval Fuzzy Kohonen Networks Algorithm in Simple Swarm Robots

A novel technique to control swarm robot’s movement is presented and analyzed in this paper. It allows a group of robots to move as a unique entity performing the following function such as obstacle avoidance at group level. The control strategy enhances the mobile robot’s performance whereby their forthcoming decisions are impacted by its previous experiences during the navigation apart from the current range inputs. Interval Fuzzy-Kohonen Network (IFKN) algorithm is utilized in this strategy. By employing a small number of rules, the IFKN algorithms can be adapted to swarms reactive control. The control strategy provides much faster response compare to Fuzzy Kohonen Network (FKN) algorithm to expected events. The effectiveness of the proposed technique is also demonstrated in a series of practical test on our experimental by using five low cost robots with limited sensor abilities and low computational effort on each single robot in the swarm. The results show that swarm robots based on proposed technique have the ability to perform cooperative behavior, produces minimum collision and capable to navigate around square shapes obstacles

Search and restore: a study of cooperative multi-robot systems

Swarm intelligence is the study of natural biological systems with the ability to transform simple local interactions into complex global behaviours. Swarm robotics takes these principles and applies them to multi-robot systems with the aim of achieving the same level of complex behaviour which can result in more robust, scalable and flexible robotic solutions than singular robot systems. This research concerns how cooperative multi-robot systems can be utilised to solve real world challenges and outperform existing techniques. The majority of this research is focused around an emergency ship hull repair scenario where a ship has taken damage and sea water is flowing into the hull, decreasing the stability of the ship. A bespoke team of simulated robots using novel algorithms enable the robots to perform a coordinated ship hull inspection, allowing the robots to locate the damage faster than a similarly sized uncoordinated team of robots. Following this investigation, a method is presented by which the same team of robots can use self-assembly to form a structure, using their own bodies as material, to cover and repair the hole in the ship hull, halting the ingress of sea water. The results from a collaborative nature-inspired scenario are also presented in which a swarm of simple robots are tasked with foraging within an initially unexplored bounded arena. Many of the behaviours implemented in swarm robotics are inspired by biological swarms including their goals such as optimal distribution within environments. In this scenario, there are multiple items of varying quality which can be collected from different sources in the area to be returned to a central depot. The aim of this study is to imbue the robot swarm with a behaviour that will allow them to achieve the most optimal foraging strategy similar to those observed in more complex biological systems such as ants. The author’s main contribution to this study is the implementation of an obstacle avoidance behaviour which allows the swarm of robots to behave more similarly to systems of higher complexity

Heterogeneous LTE/ Wi-Fi architecture for intelligent transportation systems

Intelligent Transportation Systems (ITS) make use of advanced technologies to enhance road safety and improve traffic efficiency. It is anticipated that ITS will play a vital future role in improving traffic efficiency, safety, comfort and emissions. In order to assist the passengers to travel safely, efficiently and conveniently, several application requirements have to be met simultaneously. In addition to the delivery of regular traffic and safety information, vehicular networks have been recently required to support infotainment services. Previous vehicular network designs and architectures do not satisfy this increasing traffic demand as they are setup for either voice or data traffic, which is not suitable for the transfer of vehicular traffic. This new requirement is one of the key drivers behind the need for new mobile wireless broadband architectures and technologies. For this purpose, this thesis proposes and investigates a heterogeneous IEEE 802.11 and LTE vehicular system that supports both infotainment and ITS traffic control data. IEEE 802.11g is used for V2V communications and as an on-board access network while, LTE is used for V2I communications. A performance simulation-based study is conducted to validate the feasibility of the proposed system in an urban vehicular environment. The system performance is evaluated in terms of data loss, data rate, delay and jitter. Several simulation scenarios are performed and evaluated. In the V2I-only scenario, the delay, jitter and data drops for both ITS and video traffic are within the acceptable limits, as defined by vehicular application requirements. Although a tendency of increase in video packet drops during handover from one eNodeB to another is observed yet, the attainable data loss rate is still below the defined benchmarks. In the integrated V2V-V2I scenario, data loss in uplink ITS traffic was initially observed so, Burst communication technique is applied to prevent packet losses in the critical uplink ITS traffic. A quantitative analysis is performed to determine the number of packets per burst, the inter-packet and inter-burst intervals. It is found that a substantial improvement is achieved using a two-packet Burst, where no packets are lost in the uplink direction. The delay, jitter and data drops for both uplink and downlink ITS traffic, and video traffic are below the benchmarks of vehicular applications. Thus, the results indicate that the proposed heterogeneous system offers acceptable performance that meets the requirements of the different vehicular applications. All simulations are conducted on OPNET Network Modeler and results are subjected to a 95% confidence analysis