Trophallaxis within a robotic swarm: bio-inspired communication among robots in a swarm

This article presents a bio-inspired communication strategy for large-scale robotic swarms. The strategy is based purely on robot-to-robot interactions without any central unit of communication. Thus, the emerging swarm regulates itself in a purely self-organized way. The strategy is biologically inspired by the trophallactic behavior (mouth-to-mouth feedings) performed by social insects. We show how this strategy can be used in a collective foraging scenario and how the efficiency of this strategy can be shaped by evolutionary computation. Although the algorithm works stable enough that it can be easily parameterized by hand, we found that artificial evolution could further increase the efficiency of the swarm’s behavior. We investigated the suggested communication strategy by simulation of robotic swarms in several arena scenarios and studied the properties of some of the emergent collective decisions made by the robots. We found that our control algorithm led to a nonlinear, but graduated path selection of the emerging trail of loaded robots. They favored the shortest path, but not all robots converged to this trail, except in arena setups with extreme differences in the length of the two possible paths. Finally, we demonstrate how the flexibility of collective decisions that arise through this new strategy can be used in changing environments. We furthermore show the importance of a negative feedback in an environment with changing foraging targets. Such feedback loops allow outdated information to decay over time. We found that task efficiency is constrained by a lower and an upper boundary concerning the strength of this negative feedback.     

Autonomous Vehicle Emergency Recovery Tool: A Cooperative Robotic System for Car Extraction

Vehicles have been proven to be an ideal means for terrorists because they can be meticulously prepared well in advance before being deployed in urban and public places. To increase the risk and burden of explosive ordnance disposal teams, third‐party vehicles have also been used to block the access path to the explosive loaded vehicle. In this paper, we present a multirobot system that can remove vehicles from confined spaces with delicate handling, swiftly and in any direction to a safer disposal point. The new lifting robots, capable of omnidirectional movement, autonomously underride the identified vehicle and dock to its wheels for a synchronized lifting and extraction. The validity and efficiency of the novel robotic system is illustrated via experiments in an indoor parking lot, demonstrating successful autonomous navigation, docking, lifting, and extraction of a conventional car for a total covered distance of 20 m.     

From earwigs to humans

Both direct, and evolved, behavior-based approaches to mobile robots have yielded a number of interesting demonstrations of robots that navigate, map, plan and operate in the real world. The work can best be described as attempts to emulate insect-level locomotion and navigation, with very little work on behavior-based non-trivial manipulation of the world. There have been some behavior-based attempts at exploring social interactions, but these too have been modeled after the sorts of social interactions we see in insects. But thinking how to scale from all this insect-level work to full human-level intelligence and social interactions leads to a synthesis that is very different from that imagined in traditional Artificial Intelligence and Cognitive Science. We report on work towards that goal.     

Controlling gaze with an embodied interactive control architecture

Human-Robot Interaction (HRI) is a growing field of research that targets the development of robots which are easy to operate, more engaging and more entertaining. Natural human-like behavior is considered by many researchers as an important target of HRI. Research in Human-Human communications revealed that gaze control is one of the major interactive behaviors used by humans in close encounters. Human-like gaze control is then one of the important behaviors that a robot should have in order to provide natural interactions with human partners. To develop human-like natural gaze control that can integrate easily with other behaviors of the robot, a flexible robotic architecture is needed. Most robotic architectures available were developed with autonomous robots in mind. Although robots developed for HRI are usually autonomous, their autonomy is combined with interactivity, which adds more challenges on the design of the robotic architectures supporting them. This paper reports the development and evaluation of two gaze controllers using a new cross-platform robotic architecture for HRI applications called EICA (The Embodied Interactive Control Architecture), that was designed to meet those challenges emphasizing how low level attention focusing and action integration are implemented. Evaluation of the gaze controllers revealed human-like behavior in terms of mutual attention, gaze toward partner, and mutual gaze. The paper also reports a novel Floating Point Genetic Algorithm (FPGA) for learning the parameters of various processes of the gaze controller.     

Service robot for the elderly

In recent years, service robots have received a lot of attention from both industry and academia. They are individually designed to performtasks in an unstructured environment for working with or assisting humans [1], [2]. Such robots thus have to be able to actively interact with potential users in their surroundings and to appropriately offer their services. Until now, a number of service robots have been introduced such as vacuum cleaning robots, home security robots, entertainment robots, and guide robots [2]?[4]. In particular, robots that are able to assist the elderly are becoming very important with a dramatic increase in the aging population and costs of elderly care [1], [2], [5]. Several projects have been initiated in some developed countries to develop service robots, especially robotic aid systems [2], [5].     

Tunnel passing maneuvers of prescribed formations

Tunnel passing is a pattern formation of multiple robots, an outcome of formation control which is the general problem of controlling a large number of robots required to move as a group. Tunnel passing deals with the task of driving a team of robots from arbitrary initial positions through a tunnel of given geometry. This paper proposes a decentralized planner that guarantees collision‐free tunnel passing maneuvers of a team of nonholonomic car‐like robots fixed in a prescribed formation, while considering all the practical limitations and constraints due to nonholonomy, tunnel geometry, and the formation specifications. Although solutions in literature are restricted to tunnels with linear segments, this paper introduces piecewise tunnel walls with straight and curved segments. The motion planner, derived from the Lyapunov‐based control scheme works within an overarching leader‐follower framework to generate either split/rejoin or expansion/contraction of the formation, as feasible solutions. Results from simulating virtual scenarios demonstrated the effectiveness of the proposed nonlinear controllers. Copyright © 2012 John Wiley & Sons, Ltd.     

Navigation of carlike robots in an extended dynamic environment with swarm avoidance

In this paper, we propose a new solution to the motion planning and control problem for a team of carlike mobile robots traversing in an extended dynamic environment. Motivated by the emerging necessity to avoid or defend against a swarm of autonomous robots, the wide array of obstacles in this dynamic environment for the first time includes a swarm of boids governed separately by a system of ordinary differential equations. The swarm exhibits collective emergent behaviors, whereas the carlike mobile robots safely navigate to designated targets. We present a set of nonlinear continuous controllers for obstacle, collision, and swarm avoidance. The controllers provide a collision‐free trajectory within a constrained workspace cluttered with various fixed and moving obstacles while satisfying the nonholonomic and kinodynamic constraints associated with the vehicular robotic system. An advantage of the proposed method is the ease in deriving the acceleration‐based control laws from the Lyapunov‐based control scheme. The effectiveness of the control laws is demonstrated via computer simulations. The novelty of this paper lies in the simplicity of the controllers and the ease in the treatment of an extended dynamic environment, which includes swarm avoidance.     

Introduction to the special issue on Advances in intelligent nonlinear control for robotic systems

In the last two decades, robotic systems have achieved wide applications in every aspect of human society, including industrial manufacturing, automotive production, medical devices, and social lives. With the     

From Fireflies to Fault-Tolerant Swarms of Robots

One of the essential benefits of swarm robotic systems is redundancy. In case one robot breaks down, another robot can take steps to repair the failed robot or take over the failed robot's task. Although fault tolerance and robustness to individual failures have often been central arguments in favor of swarm robotic systems, few studies have been dedicated to the subject. In this paper, we take inspiration from the synchronized flashing behavior observed in some species of fireflies. We derive a completely decentralized algorithm to detect non-operational robots in a swarm robotic system. Each robot flashes by lighting up its on-board light-emitting diodes (LEDs), and neighboring robots are driven to flash in synchrony. Since robots that are suffering catastrophic failures do not flash periodically, they can be detected by operational robots. We explore the performance of the proposed algorithm both on a real-world swarm robotic system and in simulation. We show that failed robots are detected correctly and in a timely manner, and we show that a system composed of robots with simulated self-repair capabilities can survive relatively high failure rates.      

基于FLAC~(3D)的引水隧洞主、支洞交叉部位的围岩变形分析

圆形洞室开挖后,岩体中形成一个自由空间,使原来处于挤压状态的围岩,由于失去了支撑而发生向洞内松动变形;如果这种变形超过了围岩本身所能承受的能力,则围岩就会发生破坏。本文应用有限差分法数值模拟软件FLAC3D对主、支洞交叉部位的隧洞围岩变形进行模拟分析。模拟结果表明,隧洞开挖后,围岩各部分的位移量较大,围岩应力集中在主、支洞交叉部位。     

A saliency-driven robotic head with bio-inspired saccadic behaviors for social robotics

This paper presents a robotic head for social robots to attend to scene saliency with bio-inspired saccadic behaviors. Scene saliency is determined by measuring low-level static scene information, motion, and object prior knowledge. Towards the extracted saliency spots, the designed robotic head is able to turn gazes in a saccadic manner while obeying eye–head coordination laws with the proposed control scheme. The results of the simulation study and actual applications show the effectiveness of the proposed method in discovering of scene saliency and human-like head motion. The proposed techniques could possibly be applied to social robots to improve social sense and user experience in human–robot interaction.     

Teamwork in Self-Organized Robot Colonies

Swarm robotics draws inspiration from decentralized self-organizing biological systems in general and from the collective behavior of social insects in particular. In social insect colonies, many tasks are performed by higher order group or team entities, whose task-solving capacities transcend those of the individual participants. In this paper, we investigate the emergence of such higher order entities. We report on an experimental study in which a team of physical robots performs a foraging task. The robots are “identical” in hardware and control. They make little use of memory and take actions purely on the basis of local information.      

Hybrid mission planning with coalition formation

The increase in robotic capabilities and the number of such systems being used has resulted in opportunities for robots to work alongside humans in an increasing number of domains. The current robot control paradigm of one or multiple humans controlling a single robot is not scalable to domains that require large numbers of robots and is infeasible in communications constrained environments. Robots must autonomously plan how to accomplish missions composed of many tasks in complex and dynamic domains; however, mission planning with a large number of robots for such complex missions and domains is intractable. Coalition formation can manage planning problem complexity by allocating the best possible team of robots for each task. A limitation is that simply allocating the best possible team does not guarantee an executable plan can be formulated. However, coupling coalition formation with planning creates novel, domain-independent tools resulting in the best possible teams executing the best possible plans for robots acting in complex domains.     

A reference architecture for social robots

Social robotics poses tough challenges to software designers who are required to take care of difficult architectural drivers like acceptability, trust of robots as well as to guarantee that robots establish a personalized interaction with their users. Moreover, in this context recurrent software design issues such as ensuring interoperability, improving reusability and customizability of software components also arise. Designing and implementing social robotic software architectures is a time-intensive activity requiring multi-disciplinary expertise: this makes it difficult to rapidly develop, customize, and personalize robotic solutions. These challenges may be mitigated at design time by choosing certain architectural styles, implementing specific architectural patterns and using particular technologies. Leveraging on our experience in the MARIO project, in this paper we propose a series of principles that social robots may benefit from. These principles lay also the foundations for the design of a reference software architecture for social robots. The goal of this work is twofold: (i) Establishing a reference architecture whose components are unambiguously characterized by an ontology thus allowing to easily reuse them in order to implement and personalize social robots; (ii) Introducing a series of standardized software components for social robots architecture (mostly relying on ontologies and semantic technologies) to enhance interoperability, to improve explainability, and to favor rapid prototyping.     

Development and evaluation of a Venus flytrap-inspired microrobot

Nature has provided the inspiration for many robots, leading to the development of biomimetic machines based on stick insects, jellyfish, butterflies, lobsters, and inchworms. Some carnivorous plants are capable of rapid motion, including mimosa, Venus flytraps, telegraph plants, sundews, and bladderworts, all of which are of interest in the design of biomimetic robots that can be activated in a controlled manner to capture prey using trigger hairs. Here, we describe a biomimetic robotic inspired by a Venus flytrap and fabricated using two ionic polymer metal composite (IPMC) actuators. First, we describe the structure of the robotic flytrap, which consists of two IPMC lobes and a proximity sensor, and discuss the design of the control circuitry. We then evaluate the deformation and bending force of the IPMC actuator with various applied signal voltages. We describe a prototype robotic flytrap utilising a proximity sensor to imitate the trigger hairs of the Venus flytrap. We conducted an experiment to assess the feasibility of the biomimetic flytrap. To evaluate grasping ability, we measured the maximum grasping payload with different applied voltages. To enlarge the working area, we integrated biomimetic walking and rotating motion into the robotic Venus flytrap. This paper describes a prototype movable robotic Venus flytrap and evaluates its walking and rotating speeds.     

Social development [robots]

Most robots are designed to operate in environments that are either highly constrained (as is the case in an assembly line) or extremely hazardous (such as the surface of Mars). Machine learning has been an effective tool in both of these environments by augmenting the flexibility and reliability of robotic systems, but this is often a very difficult problem because the complexity of learning in the real world introduces very high dimensional state spaces and applies severe penalties for mistakes. Human children are raised in environments that are just as complex (or even more so) than those typically studied in robot learning scenarios. However, the presence of parents and other caregivers radically changes the type of learning that is possible. Consciously and unconsciously, adults tailor their action and the environment to the child. They draw attention to important aspects of a task, help in identifying the cause of errors and generally tailor the task to the child's capabilities. Our research group builds robots that learn in the same type of supportive environment that human children have and develop skills incrementally through their interactions. Our robots interact socially with human adults using the same natural conventions that a human child would use. Our work sits at the intersection of the fields of social robotics (Fong et al., 2003; Breazeal and Scawellan, 2002) and autonomous mental development (Weng et al., 2000). Together, these two fields offer the vision of a machine that can learn incrementally, directly from humans, in the same ways that humans learn from each other. In this article, we introduce some of the challenges, goals, and applications of this research.     

Realization of a Pheromone Potential Field for Autonomous Navigation by Radio Frequency Identification

This paper presents the results of our research that aims to implement autonomous navigation with an artificial pheromone system. As social insects, a group of ants show advanced performance in their activity by using a chemical substance called a pheromone. By introducing an artificial pheromone system composed of data carriers and autonomous robots, the robotic system creates a potential field to navigate their group. Using this approach we have developed a pheromone density model to realize the function of pheromones with the help of data carriers. We intend to show the effectiveness of the proposed system by performing computer simulations and real experiments for one and two dimensions. The proposed system can be used for an autonomous navigation system. Results are discussed and future works are proposed.     

A dynamics formulation of general constrained robots

The complexity of a standard compact-in-form Lagrangian dynamical expression is proportional to the fourth power of the number of degrees of freedom (DOF) of a robotic system. This fact challenges both simulation and control of robots with hyper degrees of freedom. In this paper, a systematic approach for deriving the dynamical expression of so-called general constrained robots is proposed. This proposed approach has two main features. First, it uses the subsystem dynamics such as the dynamics of joints and rigid links to construct the dynamical expression of the entire robotic system in a closed form. The complexity of the resulted dynamic expression is linearly proportional to the number of DOF of a robotic system. Second, it extends the standard dynamical form and properties of the conventional single-arm constrained robots to a class of more general robotic systems including the coordinated multiple-arm robotic systems. Three spaces, namely the general joint space, the general task space, and the extended subsystems space, are connected through corresponding velocity/force mapping matrices.An erratum to this article can be found at     

The state of the art of testing standards for integrated robotic systems

Technology standards facilitate the transparency in market and the supplies of products with good quality. For manufacturers, standards make it possible to reduce the costs by mass production, and enhance system adaptabilities through integrating system modules with the standardized interfaces. However, International standards on industrial robots such as ISO-9283 were developed in 1998, and they have not updated since then. Due to every-increasing applications of robots in complex systems, there is an emerging need to advance existing standards on robots for a broader scope of system components and system integration. This paper gives an introduction of the endeavors by National Institute of Standards and Technology (NIST); especially, it overviews the recent progresses on the standardized tests of robotic systems and components. The presented work aims to identify the limitations of existing industrial standards and clarify the trend of technology standardizations for industrial robotic systems.     

Agent-based control for fuzzy behavior programming in robotic excavation

This paper discusses the concept, formulation, and implementation of the agent-based control for fuzzy behavior programming in robotic excavation. Petri net transducers are introduced to describe excavation control agent coordination and specification, while fuzzy control rules are used to implement primitive motions. A prototype laboratory excavation system is built with PUMA robotic manipulators and a force/torque sensor. Extensive experiments have been conducted and the results have demonstrated that the proposed control method is capable of continuously adapting and replanning its actions based on sensory feedback, and completing its excavation tasks in dynamic and unstructured environments.