Designing pheromone communication in swarm robotics: Group foraging behavior mediated by chemical substance

In swarm robotics, communication among the robots is essential. Inspired by biological swarms using pheromones, we propose the use of chemical compounds to realize group foraging behavior in robot swarms. We designed a fully autonomous robot, and then created a swarm using ethanol as the trail pheromone allowing the robots to communicate with one another indirectly via pheromone trails. Our group recruitment and cooperative transport algorithms provide the robots with the required swarm behavior. We conducted both simulations and experiments with real robot swarms, and analyzed the data statistically to investigate any changes caused by pheromone communication in the performance of the swarm in solving foraging recruitment and cooperative transport tasks. The results show that the robots can communicate using pheromone trails, and that the improvement due to pheromone communication may be non-linear, depending on the size of the robot swarm.     

Artificial pheromone for path selection by a foraging swarm of robots

Foraging robots involved in a search and retrieval task may create paths to navigate faster in their environment. In this context, a swarm of robots that has found several resources and created different paths may benefit strongly from path selection. Path selection enhances the foraging behavior by allowing the swarm to focus on the most profitable resource with the possibility for unused robots to stop participating in the path maintenance and to switch to another task. In order to achieve path selection, we implement virtual ants that lay artificial pheromone inside a network of robots. Virtual ants are local messages transmitted by robots; they travel along chains of robots and deposit artificial pheromone on the robots that are literally forming the chain and indicating the path. The concentration of artificial pheromone on the robots allows them to decide whether they are part of a selected path. We parameterize the mechanism with a mathematical model and provide an experimental validation using a swarm of 20 real robots. We show that our mechanism favors the selection of the closest resource is able to select a new path if a selected resource becomes unavailable and selects a newly detected and better resource when possible. As robots use very simple messages and behaviors, the system would be particularly well suited for swarms of microrobots with minimal abilities.     

Self-organized cooperation between robotic swarms

We study self-organized cooperation between heterogeneous robotic swarms. The robots of each swarm play distinct roles based on their different characteristics. We investigate how the use of simple local interactions between the robots of the different swarms can let the swarms cooperate in order to solve complex tasks. We focus on an indoor navigation task, in which we use a swarm of wheeled robots, called foot-bots, and a swarm of flying robots that can attach to the ceiling, called eye-bots. The task of the foot-bots is to move back and forth between a source and a target location. The role of the eye-bots is to guide foot-bots: they choose positions at the ceiling and from there give local directional instructions to foot-bots passing by. To obtain efficient paths for foot-bot navigation, eye-bots need on the one hand to choose good positions and on the other hand learn the right instructions to give. We investigate each of these aspects. Our solution is based on a process of mutual adaptation, in which foot-bots execute instructions given by eye-bots, and eye-bots observe the behavior of foot-bots to adapt their position and the instructions they give. Our approach is inspired by pheromone mediated navigation of ants, as eye-bots serve as stigmergic markers for foot-bot navigation. Through simulation, we show how this system is able to find efficient paths in complex environments, and to display different kinds of complex and scalable self-organized behaviors, such as shortest path finding and automatic traffic spreading.     

Robot Pheromone Communication Using Vortex Ring Transmission

Unpredictable air movements have proved to be a problem in previous studies investigating robot communication bymeans of airborne pheromone chemicals. The project described in this paper investigates the use of air vortex rings as a means ofcarrying pheromone chemicals between transmitting and receiving robots. Sensitivity to chemicals including pheromonesreleased by conspecifics is essential for many aspects of an insect’s life. They assist in finding food, locating a mate, avoidingdanger and help coordinate the activities of social insects. In the future, autonomous robots will be challenged by many situationssimilar to those that face insects and other simple creatures. Chemical communication may prove useful for these robots aswell. This paper describes the equipment developed for generating and detecting vortex rings. Results of experiments involvinglocation and tracking of a sequence of pheromone vortex rings are also presented.     

Cooperative navigation in robotic swarms

We study cooperative navigation for robotic swarms in the context of a general event-servicing scenario. In the scenario, one or more events need to be serviced at specific locations by robots with the required skills. We focus on the question of how the swarm can inform its members about events, and guide robots to event locations. We propose a solution based on delay-tolerant wireless communications: by forwarding navigation information between them, robots cooperatively guide each other towards event locations. Such a collaborative approach leverages on the swarm’s intrinsic redundancy, distribution, and mobility. At the same time, the forwarding of navigation messages is the only form of cooperation that is required. This means that the robots are free in terms of their movement and location, and they can be involved in other tasks, unrelated to the navigation of the searching robot. This gives the system a high level of flexibility in terms of application scenarios, and a high degree of robustness with respect to robot failures or unexpected events. We study the algorithm in two different scenarios, both in simulation and on real robots. In the first scenario, a single searching robot needs to find a single target, while all other robots are involved in tasks of their own. In the second scenario, we study collective navigation: all robots of the swarm navigate back and forth between two targets, which is a typical scenario in swarm robotics. We show that in this case, the proposed algorithm gives rise to synergies in robot navigation, and it lets the swarm self-organize into a robust dynamic structure. The emergence of this structure improves navigation efficiency and lets the swarm find shortest paths.     

Artificial gills for robots: MFC behaviour in water

This paper reports on the first stage in developing microbial fuel cells (MFCs) which can operate underwater by utilizing dissolved oxygen. In this context, the cathodic half-cell is likened to an artificial gill. Such an underwater power generator has obvious potential for autonomous underwater robots. The electrical power from these devices increased proportionately with water flow rate, temperature and salinity. The current output at ambient temperature (null condition) was 32 microA and this increased by 200% (approximately 100 microA) as a result of a corresponding temperature increase (DeltaT) of 52 degrees C. Similarly, the effect of increasing the water flow rate resulted in an increase in the MFC output ranging from 135% to 150%. Furthermore, the same positive effect was recorded when artificial seawater was used instead, in which case the increase in the MFC current output was >100% (from 32 to 65 microA). There was a distinct difference in the MFC performance when operated under low turbulent as opposed to high turbulent flow rates. These findings can be advantageous in the design of underwater autonomous robots.     

Swarm cognition on off-road autonomous robots

This paper contributes with the first validation of swarm cognition as a useful framework for the design of autonomous robots controllers. The proposed model is built upon the authors’ previous work validated on a simulated robot performing local navigation on a 2-D deterministic world. Based on the ant foraging metaphor and motivated by the multiple covert attention hypothesis, the model consists of a set of simple virtual agents inhabiting the robot’s visual input, searching in a collectively coordinated way for obstacles. Parsimonious and accurate visual attention, operating on a by-need basis, is attained by making the activity of these agents modulated by the robot’s action selection process. A by-product of the system is the maintenance of active, parallel and sparse spatial working memories. In short, the model exhibits the self-organisation of a relevant set of features composing a cognitive system. To show its robustness, the model is extended in this paper to handle the challenges of physical off-road robots equipped with noisy stereoscopic vision sensors. Furthermore, an extensive aggregate of biological arguments sustaining the model is provided. Experimental results show the ability of the model to robustly control the robot on a local navigation task, with less than 1% of the robot’s visual input being analysed. Hence, with this system the computational cost of perception is considerably reduced, thus fostering robot miniaturisation and energetic efficiency. This confirms the advantages of using a swarm-based system, operating in an intricate way with action selection, to judiciously control visual attention and maintain sparse spatial memories, constituting a basic form of swarm cognition.     

Multiphasic On/Off Pheromone Signalling in Moths as Neural Correlates of a Search Strategy

Insects and robots searching for odour sources in turbulent plumes face the same problem: the random nature of mixing causes fluctuations and intermittency in perception. Pheromone-tracking male moths appear to deal with discontinuous flows of information by surging upwind, upon sensing a pheromone patch, and casting crosswind, upon losing the plume. Using a combination of neurophysiological recordings, computational modelling and experiments with a cyborg, we propose a neuronal mechanism that promotes a behavioural switch between surge and casting. We show how multiphasic On/Off pheromone-sensitive neurons may guide action selection based on signalling presence or loss of the pheromone. A Hodgkin-Huxley-type neuron model with a small-conductance calcium-activated potassium (SK) channel reproduces physiological On/Off responses. Using this model as a command neuron and the antennae of tethered moths as pheromone sensors, we demonstrate the efficiency of multiphasic patterning in driving a robotic searcher toward the source. Taken together, our results suggest that multiphasic On/Off responses may mediate olfactory navigation and that SK channels may account for these responses.     

Stingless bees (<Emphasis Type="Italic">Scaptotrigona pectoralis</Emphasis>) learn foreign trail pheromones and use them to find food

Foragers of several species of stingless bees (Hymenoptera, Apidae and Meliponini) deposit pheromone marks in the vegetation to guide nestmates to new food sources. These pheromones are produced in the labial glands and are nest and species specific. Thus, an important question is how recruited foragers recognize their nestmates’ pheromone in the field. We tested whether naïve workers learn a specific trail pheromone composition while being recruited by nestmates inside the hive in the species Scaptotrigona pectoralis. We installed artificial scent trails branching off from trails deposited by recruiting foragers and registered whether newly recruited bees follow these trails. The artificial trails were baited with trail pheromones of workers collected from foreign S. pectoralis colonies. When the same foreign trail pheromone was presented inside the experimental hives while recruitment took place a significant higher number of bees followed the artificial trails than in experiments without intranidal presentation. Our results demonstrate that recruits of S. pectoralis can learn the composition of specific trail pheromone bouquets inside the nest and subsequently follow this pheromone in the field. We, therefore, suggest that trail pheromone recognition in S. pectoralis is based on a flexible learning process rather than being a genetically fixed behaviour.     

Self-organisation and communication in groups of simulated and physical robots

In social insects, both self-organisation and communication play a crucial role for the accomplishment of many tasks at a collective level. Communication is performed with different modalities, which can be roughly classified into three classes: indirect (stigmergic) communication, direct interactions and direct communication. The use of stigmergic communication is predominant in social insects (e.g. the pheromone trails in ants), where, however, direct interactions (e.g. antennation in ants) and direct communication (e.g. the waggle dance in honey bees) can also be observed. Taking inspiration from insect societies, we present an experimental study of self-organising behaviours for a group of robots, which exploit communication to coordinate their activities. In particular, the robots are placed in an arena presenting holes and open borders, which they should avoid while moving coordinately. Artificial evolution is responsible for the synthesis in a simulated environment of the robot’s neural controllers, which are subsequently tested on physical robots. We study different communication strategies among the robots: no direct communication, handcrafted signalling and a completely evolved approach. We show that the latter is the most efficient, suggesting that artificial evolution can produce behaviours that are more adaptive than those obtained with conventional design methodologies. Moreover, we show that the evolved controllers produce a self-organising system that is robust enough to be tested on physical robots, notwithstanding the huge gap between simulation and reality.Electronic Supplementary Material Supplementary material is available for this article at     

Performance evaluation of a machine vision system for insect pests identification of field crops using artificial neural networks

Feature extraction is a crucial part of advanced image recognition systems. In this research, an autonomous detection device was designed and developed for insect pest detection to improve the ability of intelligent systems in order to annihilate harmful insect pests in agricultural crop fields. Device included a dark chamber, a CCD digital camera, a LDR lightening module and a personal computer. The proposed programme for precise insect pest detection was based on an image processing algorithm and artificial neural networks (ANNs). After image acquisition, the insect pests’ images were extracted from original images with Canny filtration. Afterwards, four morphological and three textural features from the obtained images were measured and normalised. Performance of ANN model was tested successfully for Beet armyworm (Spodoptera exigua) recognition in images using back-propagation supervised learning method and inspection data. Results showed that proposed system was able to identify S. exigua in the images from other species. Such this machine vision system can be used in autonomous field robots to achieve a modern farmer’s assistant.     

昆虫信息化学物质的应用进展

介绍昆虫性信息素(sex pheromone)、示踪信息素(trail pheromone)、聚集信息素(aggregation pheromone)、产卵(oviposition)和产卵忌避(oviposition deterring)信息化合物(semioche micals)和种间协同素(synomone)在害虫控制方面的最新应用进展,其中,重点介绍性信息素在害虫种群监测、大量诱捕和干扰交配3个方面的应用进展情况。与性信息素相比,人们对示踪信息素、聚集信息素、产卵和产卵忌避信息化合物和种间协同素的报道较少,但这些信息素也正在不断的被人们发现和利用。从一种昆虫信息素被鉴定出来,到其在生产当中很好应用,尚有很多问题需要解决,所以,文中对昆虫信息化学物质田间应用效果的影响因子进行分析。     

Concept of Intelligent Mechanical Design for Autonomous Mobile Robots

The concept of Intelligent Mechanical Design (IMD) is presented to show how a mechanical structure can be designed to affect robot controllability, simplification and task performance. Exploring this concept produces landmarks in the territory of mechanical robot design in the form of seven design principles. The design principles, which we call the Mecha-Telligence Principles (MTP), provide guidance on how to design mechanics for autonomous mobile robots. These principles guide us to ask the right questions when investigating issues concerning self-controllable, reliable, feasible, and compatible mechanics for autonomous mobile robots. To show how MTP can be applied in the design process we propose a novel methodology, named as Mecha-Telligence Methodology (MTM). Mechanical design by the proposed methodology is based on preference classification of the robot specification described by interaction of the robot with its environment and the physical parameters of the robot mechatronics. After defining new terms, we investigate the feasibility of the proposed methodology to the mechanical design of an autonomous mobile sewer inspection robot. In this industrial project we show how a passive-active intelligent moving mechanism can be designed using the MTM and employed in the field.     

Visual guidance based on optic flow: a biorobotic approach.

This paper addresses some basic questions as to how vision links up with action and serves to guide locomotion in both biological and artificial creatures. The thorough knowledge gained during the past five decades on insects' sensory-motor abilities and the neuronal substrates involved has provided us with a rich source of inspiration for designing tomorrow's self-guided vehicles and micro-vehicles, which will be able to cope with unforeseen events on the ground, under water, in the air, in space, on other planets, and inside the human body. Insects can teach us some useful tricks for designing agile autonomous robots. Since constructing a "biorobot" first requires exactly formulating the biological principles presumably involved, it gives us a unique opportunity of checking the soundness and robustness of these principles by bringing them face to face with the real physical world. "Biorobotics" therefore goes one step beyond computer simulation. It leads to experimenting with real physical robots which have to pass the stringent test of the real world. Biorobotics provide us with a new tool, which can help neurobiologists and neuroethologists to identify and investigate worthwhile issues in the field of sensory-motor control. Here we describe some of the visually guided terrestrial and aerial robots we have developed since 1985 on the basis of our biological findings. All these robots behave in response to the optic flow, i.e., they work by measuring the slip speed of the retinal image. Optic flow is sensed on-board by miniature electro-optical velocity sensors. The very principle of these sensors was based on studies in which we recorded the responses of single identified neurons to single photoreceptor stimulation in a model visual system: the fly's compound eye.     

Behaviour of pink bollworm males near high-dose, point sources of pheromone in field wind tunnels: insights into mechanisms of mating disruption

The mechanisms by which the application of formulated pheromone interferes with mating in the pink bollworm moth (PBW), Pectinophora gossypiella were examined in 0.4 ha cotton fields using high-dose (78 mg A.I.) sealed polyethylene dispensers. Walk-in, field wind tunnels 6.2 m long were placed over two rows of cotton. Treatments consisted of a control, a tunnel in a field free of disruptant formulation; a 3-rope treatment, in which the field was free of pheromone but one of the cotton rows in the wind tunnel was treated with 3 PBW ropes; and a rope-grid treatment, in which the field was treated with PBW ropes at the standard density of 1000 ha–1 and one of the cotton rows inside the wind tunnel was treated with 3 PBW ropes. We released marked males into the tunnels near sunset or held them in field cages for 24 h prior to assay. Two pheromone traps at the tunnel's upwind end monitored the ability of males to locate point sources of pheromone. In the 3-rope tunnel, traps placed upwind of the cotton row treated with disruptant pheromone captured far fewer males than those placed upwind of the untreated cotton row. In the tunnel situated in the centre of the rope-gridded field, very few males were caught in traps in both rows, indicating a camouflage of the pheromone plumes from the traps by the background of airborne disruptant drawn into the tunnel from the field. Activity of moths near the synthetic pheromone sources was video-recorded. Males oriented to, landed on or near, and walked on or near, PBW ropes, indicating competition between pheromone sources as a mechanism of mating disruption. Most males visiting PBW ropes became quiescent or disappeared from the field of view after a few minutes, suggesting a habituation/adaptation of response. The rhythm of attraction of males held in the field for 24 h before release was comprised of a small peak of activity near 2000 h, with the majority of attraction between 2300 and 0300 h. Much of the attraction before 0100 appears to be an advancement of the male's normal diel rhythm, caused by the presence of disruptant. Together these findings indicate that mating disruption of pink bollworm using the PBW ropes is achieved by a combination of mechanisms: a camouflage of natural plumes, competition between pheromone sources, habituation, and some advancement of the male's rhythm of response.     

An ant navigation model based on Weber’s law

Journal of Mathematical Biology - We analyze an ant navigation model based on Weber’s law, where the ants move across a pheromone landscape sensing the area using two antennae. The key...     

From network-to-antibody robustness in a bio-inspired immune system

Behavioural robustness at antibody and immune network level is discussed. The robustness of the immune response that drives an autonomous mobile robot is examined with two computational experiments in the autonomous mobile robots trajectory generation context in unknown environments. The immune response is met based on the immune network metaphor for different low-level behaviours coordination. These behaviours are activated when a robot sense the appropriate conditions in the environment in relation to the network current state. Results are obtained over a case study in computer simulation as well as in laboratory experiments with a Khepera II microrobot. In this work, we develop a set of tests where such an immune response is externally perturbed at network or low-level behavioural modules to analyse the robust capacity of the system to unexpected perturbations. Emergence of robust behaviour and high-level immune response relates to the coupling between behavioural modules that are selectively engaged with the environment based on immune response. Experimental evidence leads discussions on a dynamical systems perspective of behavioural robustness in artificial immune systems that goes beyond the isolated immune network response.     

A System Design Concept Based on Omni-Directional Mobility,Safety and Modularity for an Autonomous Mobile Soccer Robot

In this paper, we describe the concept, design and implementation of a series of autonomous mobile soccer robots, named Musashi robots, which are designed referring ISO safety standards and have mechatronics modular architecture. The robots are designed to participate in the RoboCup Middle Size League. Using a modular design philosophy, we show that the selection of a proper moving mechanism, a suitable vision system and a mechatronics modular architecture design can lead to the realization of a reliable, simple, and low cost robot when compared with most car-like robots that include many kinds of sensors and have a complex design structure.     

Pheromonal cross-attraction in true bugs (Heteroptera): attraction of Piezodorus hybneri (Pentatomidae) to its pheromone versus the pheromone of Riptortus pedestris (Alydidae)

We investigated the attractiveness of a synthetic form of the pheromone of the soybean stink bug, Piezodorus hybneri (Gmelin), under field conditions, and compared it with that of (E)-2-hexenyl (E)-2-hexenoate, a pheromone component of a competitor, Riptortus pedestris (Fabricius). Many adult stink bugs were attracted to traps baited with 100 mg of the synthetic pheromone (1: 1: one mixture of β-sesquiphellandrene, (R)-15-hexadecanolide, and methyl (Z)-8-hexadecenoate), but few were attracted to 1 or 10 mg. More than twice as many females as males were attracted to this male-produced pheromone. None of the individual pheromone components (30 mg) attracted conspecifics. In summer (June-July), when field P. hybneri were not in diapause, (E)-2-hexenyl (E)-2-hexenoate was more attractive to P. hybneri than the synthetic pheromone. The sex ratio of the adults attracted to the synthetic pheromone was highly female-biased, yet almost equal numbers of both sexes were attracted to (E)-2-hexenyl (E)-2-hexenoate. Most females attracted to both attractants were mated and had mature ovaries. However, adults attracted to (E)-2-hexenyl (E)-2-hexenoate were likely to have less food in their stomach than those attracted to the synthetic pheromone. In late autumn (October-November), when the bugs were in reproductive diapause, both attractants attracted many sexually immature female and male adults that had well-developed fat body. The synthetic pheromone also attracted a large number of conspecific nymphs. These results suggest that P. hybneri pheromone and R. pedestris pheromone component, respectively, have different functions for P. hybneri. The male-produced pheromone system of P. hybneri seems to be sex-related but to have other roles.