Cooperative Object Transport in Multi-robot Systems:A Review of the State-of-the-Art

In recent years, there has been a growing interest in designing multi-robot systems (hereafter MRSs) to provide cost effective, fault-tolerant and reliable solutions to a variety of automated applications. Here, we review recent advancements in MRSs specifically designed for cooperative object transport, which requires the members of MRSs to coordinate their actions to transport objects from a starting position to a final destination. To achieve cooperative object transport, a wide range of transport, coordination and control strategies have been proposed. Our goal is to provide a comprehensive summary for this relatively heterogeneous and fast-growing body of scientific literature. While distilling the information, we purposefully avoid using hierarchical dichotomies, which have been traditionally used in the field of MRSs. Instead, we employ a coarse-grain approach by classifying each study based on the transport strategy used; pushing-only, grasping and caging. We identify key design constraints that may be shared among these studies despite considerable differences in their design methods. In the end, we discuss several open challenges and possible directions for future work to improve the performance of the current MRSs. Overall, we hope to increase the visibility and accessibility of the excellent studies in the field and provide a framework that helps the reader to navigate through them more effectivelypublishersversionPeer reviewe

A Demonstration in communication and task completion between two autonomous robots

The world of robotics is rapidly changing. No more are the days of robotics classes being taught that focus merely on highly industrial, automation robots. Today\u27s robotics is focusing more and more on microcontrollers and their implementation into everyday life. Miniature robotics and how it is implemented to make common tasks easier is becoming the focus of many robotics classes across the world. Microcontrollers allow users to control several inputs and outputs to complete somewhat difficult tasks. In today\u27s society, one might find a microcontroller in anything from a computer to the average household toaster. As time has passed, microcontrollers have become more powerful with an increased ability to control more and more inputs and outputs. In many industries, pipe inspection is critical to success. Leaks and cracks in pipes and tubes can lead to multisystem failure. Sometimes the pipes can be impossible to inspect with the human eye due to their length and location. Rather than use an umbilical corded system that would require many feet or miles of cable, it is highly desirable to create a wireless system to complete the task of pipe inspection and repair. The purpose of this project is to utilize microcontrollers to control two robots to complete the following tasks: Locate a hole in a random length of piping. Communicate the hole position between the two robots. Simulate the sealing process of the hole. Through the completion of the above-mentioned goals, this project marked the beginning of the Laboratory of Autonomous Cooperative Microsystems (LACOMS) at Rochester Institute of Technology. The final version of this project will allow for wireless communication between two robots, making the task doable with no human interference, and hence, the two robots will be totally autonomous. Future versions of this project can then focus on miniaturization of the current work on a MEMS scale

SWARM INTELLIGENCE AND STIGMERGY: ROBOTIC IMPLEMENTATION OF FORAGING BEHAVIOR

Swarm intelligence in multi-robot systems has become an important area of research within collective robotics. Researchers have gained inspiration from biological systems and proposed a variety of industrial, commercial, and military robotics applications. In order to bridge the gap between theory and application, a strong focus is required on robotic implementation of swarm intelligence. To date, theoretical research and computer simulations in the field have dominated, with few successful demonstrations of swarm-intelligent robotic systems. In this thesis, a study of intelligent foraging behavior via indirect communication between simple individual agents is presented. Models of foraging are reviewed and analyzed with respect to the system dynamics and dependence on important parameters. Computer simulations are also conducted to gain an understanding of foraging behavior in systems with large populations. Finally, a novel robotic implementation is presented. The experiment successfully demonstrates cooperative group foraging behavior without direct communication. Trail-laying and trail-following are employed to produce the required stigmergic cooperation. Real robots are shown to achieve increased task efficiency, as a group, resulting from indirect interactions. Experimental results also confirm that trail-based group foraging systems can adapt to dynamic environments

Organisation of foraging in ants

In social insects, foraging is often cooperative, and so requires considerable organisation. In most ants, organisation is a bottom-up process where decisions taken by individuals result in emergent colony level patterns. Individuals base their decisions on their internal state, their past experience, and their environment. By depositing trail pheromones, for example, ants can alter the environment, and thus affect the behaviour of their nestmates. The development of emergent patterns depends on both how individuals affect the environment, and how they react to changes in the environment. Chapters 4 – 9 investigate the role of trail pheromones and route memory in the ant Lasius niger. Route memories can form rapidly and be followed accurately, and when route memories and trail pheromones contradict each other, ants overwhelmingly follow route memories (chapter 4). Route memories and trail pheromones can also interact synergistically, allowing ants to forage faster without sacrificing accuracy (chapter 5). Home range markings also interact with other information sources to affect ant behaviour (chapter 6). Trail pheromones assist experienced ants when facing complex, difficult-to-learn routes (chapter 7). When facing complicated routes, ants deposit more pheromone to assist in navigation and learning (chapter 7). Deposition of trail pheromones is suppressed by ants leaving a marked path (chapter 5), strong pheromone trails (chapter 7) and trail crowding (chapter 8). Colony level ‘decisions’ can be driven by factors other than trail pheromones, such as overcrowding at a food source (chapter 9). Chapter 10 reviews the many roles of trail pheromones in ants. Chapters 11 – 14 focus on the organisation of cooperative food retrieval. Pheidole oxyops workers arrange themselves non-randomly around items to increase transport speeds (chapter 11). Groups of ants will rotate food items to reduce drag (chapter 12). Chapters 13 and 14 encompass the ecology of cooperative transport, and how it has shaped trail pheromone recruitment in P. oxyops and Paratrechina longicornis. Lastly, chapter 15 provide a comprehensive review of cooperative transport in ants and elsewhere

Ant colonies: building complex organizations with minuscule brains and no leaders

Thus far the articles in the series JOD calls the “Organization Zoo” have employed the notion of a “zoo” metaphorically to describe an array of human institutions. Here we take the term literally to consider the design of the most complex organizations in the living world beside those of humans, a favorite of insect zoos around the world: ant colonies. We consider individuality and group identity in the functioning of ant organizations; advantages of a flat organization without hierarchies or leaders; self-organization; direct and indirect communication; job specialization; labor coordination; and the role of errors in innovation. The likely value and limitations of comparing ant and human organizations are briefly examined

The development and implementation of an ionic-polymer-metal-composite propelled vessel guided by a goal-seeking algorithm

This thesis describes the use of an ultrasonic goal-seeking algorithm while using ionic polymer metal composite (IPMC), an electroactive polymer, as the actuator to drive a vessel towards a goal. The signal transmitting and receiving circuits as well as the goal seeking algorithm are described in detail. Two test vessels were created; one was a larger vessel that contained all necessary components for autonomy. The second was a smaller vessel that contained only the sensors and IPMC strips, and all power and signals were transmitted via an umbilical cord. To increase the propulsive efforts of the second, smaller vessel, fins were added to the IPMC strips, increasing the surface area over 700%, determined to yield a 22-fold force increase. After extensive testing, it was found that the three IPMC strips, used as oscillating fins, could not generate enough propulsion to move either vessel, with or without fins. With the addition of fins, the oscillating frequency was reduced from 0.86-Hz to 0.25-Hz. However, the goal-seeking algorithm was successful in guiding the vessel towards the target, an ultrasonic transmitter. When moved manually according to the instructions given by the algorithm, the vessel successfully reached the goal. Using assumptions based on prior experiments regarding the speed of an IPMC propelled vessel, the trial in which the goal was to the left of the axis required 18.2% more time to arrive at the goal than the trial in which the goal was to the right. This significant difference is due to the goal-seeking algorithmâÂÂs means to acquire the strongest signal. After the research had concluded and the propulsors failed to yield desired results, many factors were considered to rationalize the observations. The operating frequency was reduced, and it was found that, by the impulse-momentum theorem, that the propulsive force was reduced proportionally. The literature surveyed addressed undulatory motion, which produces constant propulsive force, not oscillatory, which yields intermittent propulsive force. These reasons among others were produced to rationalize the results and prove the cause of negative results was inherent to the actuators themselves. All rational options have been considered to yield positive results

Communication visuelle par signalement lumineux avec un robot mobile

Concevoir un robot mobile autonome pouvant opérer dans des environnements courants est un défi de taille. Il demande au robot de faire face à une variété de situations dans des conditions dynamiques et imprévisibles, et ce avec des moyens limités pour la perception, le traitement et l'action. Le robot est aussi sujet à devoir interagir avec d'autres intervenants, humains, robotiques ou autres. À cette fin, la communication s'avère une capacité intéressante pour interagir avec les autres et pour obtenir des informations venant contrer certaines des limitations du robot. La communication avec les robots s'effectue habituellement par lien électronique. Cette façon de faire permet de transmettre une grande quantité de données, mais ne donne pas en soi des indications importantes sur le contexte des informations transmises (comme par exemple la position relative de l'interlocuteur). Une autre possibilité, une communication par voie visuelle est une nouvelle approche, technologiquement réalisable, qui permet de fournir des informations additionnelles aux messages échangés. Le présent mémoire décrit un mécanisme de communication par signalement lumineux qui fut développé dans le but d'étudier les avantages et les inconvénients de la communication visuelle comme moyen d'interaction entre un robot et son entourage. La validation pratique du mécanisme avec un robot Pioneer I est aussi présentée dans le cadre d'expériences demandant au robot d'interagir avec un intervenant humain

Drama, a connectionist model for robot learning: experiments on grounding communication through imitation in autonomous robots

The present dissertation addresses problems related to robot learning from demonstra¬ tion. It presents the building of a connectionist architecture, which provides the robot with the necessary cognitive and behavioural mechanisms for learning a synthetic lan¬ guage taught by an external teacher agent. This thesis considers three main issues: 1) learning of spatio-temporal invariance in a dynamic noisy environment, 2) symbol grounding of a robot's actions and perceptions, 3) development of a common symbolic representation of the world by heterogeneous agents.We build our approach on the assumption that grounding of symbolic communication creates constraints not only on the cognitive capabilities of the agent but also and especially on its behavioural capacities. Behavioural skills, such as imitation, which allow the agent to co-ordinate its actionn to that of the teacher agent, are required aside to general cognitive abilities of associativity, in order to constrain the agent's attention to making relevant perceptions, onto which it grounds the teacher agent's symbolic expression. In addition, the agent should be provided with the cognitive capacity for extracting spatial and temporal invariance in the continuous flow of its perceptions. Based on this requirement, we develop a connectionist architecture for learning time series. The model is a Dynamical Recurrent Associative Memory Architecture, called DRAMA. It is a fully connected recurrent neural network using Hebbian update rules. Learning is dynamic and unsupervised. The performance of the architecture is analysed theoretically, through numerical simulations and through physical and simulated robotic experiments. Training of the network is computationally fast and inexpensive, which allows its implementation for real time computation and on-line learning in a inexpensive hardware system. Robotic experiments are carried out with different learning tasks involving recognition of spatial and temporal invariance, namely landmark recognition and prediction of perception-action sequence in maze travelling.The architecture is applied to experiments on robot learning by imitation. A learner robot is taught by a teacher agent, a human instructor and another robot, a vocabulary to describe its perceptions and actions. The experiments are based on an imitative strategy, whereby the learner robot reproduces the teacher's actions. While imitating the teacher's movements, the learner robot makes similar proprio and exteroceptions to those of the teacher. The learner robot grounds the teacher's words onto the set of common perceptions they share. We carry out experiments in simulated and physical environments, using different robotic set-ups, increasing gradually the complexity of the task. In a first set of experiments, we study transmission of a vocabulary to designate actions and perception of a robot. Further, we carry out simulation studies, in which we investigate transmission and use of the vocabulary among a group of robotic agents. In a third set of experiments, we investigate learning sequences of the robot's perceptions, while wandering in a physically constrained environment. Finally, we present the implementation of DRAMA in Robota, a doll-like robot, which can imitate the arms and head movements of a human instructor. Through this imitative game, Robota is taught to perform and label dance patterns. Further, Robota is taught a basic language, including a lexicon and syntactical rules for the combination of words of the lexicon, to describe its actions and perception of touch onto its body