Study on Decentralization of Spherical Amphibious Multi-robot Control System Based on Smart Contract and Blockchain

With the development of intelligent bionic robots and the improvement of military application,a single robot cannot meet the requirements of the tasks of the current era.The more complex tasks require not only that the robot be able to pass through the field barriers and the amphibious environment,but also that the robot be able to collaborate in a multi-robot system.Consequently,research on the multi-robot control system of spherical amphibious robots is very important.Pres-ently,the main research on amphibious robots is to improve the functions of a single robot,in the absence of the study of the multi-robot control system.Existing systems primarily use a centralized control methodology.Although the transfer of central node can be achieved,there is still a problem of Byzantine fault tolerance in military applications,that is,when the amphibious multi-robot system is invaded by the enemy.The central node may not only fail to accomplish the task,but also lose control of other robots,with severe consequences.To solve the above problems,this paper proposed a decentralized method of spherical amphibious multi-robot control system based on blockchain technology.First,the point-to-point informa-tion network based on long range radio technology of low power wide area network was set up,we designed the blockchain system for embedded application environment and the decentralized hardware and software architecture of multi-robot control system.On this basis,the consensus plugin,smart contract and decentralized multi-robot control algorithm were designed to achieve decentralization.The experimental results of consensus of spherical amphibious multi-robot showed the effectiveness of the decentralization.     

Using insects to drive mobile robots — hybrid robots bridge the gap between biological and artificial systems

The use of mobile robots is an effective method of validating sensory–motor models of animals in a real environment. The well-identified insect sensory–motor systems have been the major targets for modeling. Furthermore, mobile robots implemented with such insect models attract engineers who aim to avail advantages from organisms. However, directly comparing the robots with real insects is still difficult, even if we successfully model the biological systems, because of the physical differences between them. We developed a hybrid robot to bridge the gap. This hybrid robot is an insect-controlled robot, in which a tethered male silkmoth (Bombyx mori) drives the robot in order to localize an odor source. This robot has the following three advantages: 1) from a biomimetic perspective, the robot enables us to evaluate the potential performance of future insect-mimetic robots; 2) from a biological perspective, the robot enables us to manipulate the closed-loop of an onboard insect for further understanding of its sensory–motor system; and 3) the robot enables comparison with insect models as a reference biological system. In this paper, we review the recent works regarding insect-controlled robots and discuss the significance for both engineering and biology.     

Development of a robot arm and workstation for the disabled

A robotic workstation for the severely physically disabled is being developed. The prototype system consists of a commercially available arm mounted in a workstation set up for various manipulative tasks. This system has been tested with eight disabled users in a hospital situation and is to undergo evaluation in the homes of disabled users. Based on experience with this system, a new arm has been designed and will be built into a redesigned workstation.     

Development of Architectures for Internet Telerobotics Systems

This paper presents our experience in developing and implementing Internet telerobotics system. Internet telerobotics system refers to a robot system controlled and monitored remotely through the Internet. A robot manipulator with five degrees of freedom, called Mentor, is employed. Client-server architecture is chosen as a platform for our Internet telerobotics system. Three generations of telerobotics systems have evolved in this research. The first generation was based on CGI and two tiered architectures, where a client presents a Graphical User Interface to the user, and utilizes the user＇s data entry and actions to perform requests to robot server running on a different machine. The second generation was developed using Java. We also employ Java 3D for creating and manipulating 3D geometry of manipulator links, and for constructing the structures used in rendering that geometry, resulting in 3D robot movement simulation presented to the users （clients） through their web browser. Recent development in our Internet telerobotics includes object recognition through image captured by a camera, which poses challenging problem, giving the undeterministic latency of the Internet. The third generation is centered around the use of CORBA for development platform of distributed internet telerobotics system, aimed at distributing task of telerobotics system.     

A biologically inspired neural net for trajectory formation and obstacle avoidance

In this paper we present a biologically inspired two-layered neural network for trajectory formation and obstacle avoidance. The two topographically ordered neural maps consist of analog neurons having continuous dynamics. The first layer, the sensory map, receives sensory information and builds up an activity pattern which contains the optimal solution (i.e. shortest path without collisions) for any given set of current position, target positions and obstacle positions. Targets and obstacles are allowed to move, in which case the activity pattern in the sensory map will change accordingly. The time evolution of the neural activity in the second layer, the motor map, results in a moving cluster of activity, which can be interpreted as a population vector. Through the feedforward connections between the two layers, input of the sensory map directs the movement of the cluster along the optimal path from the current position of the cluster to the target position. The smooth trajectory is the result of the intrinsic dynamics of the network only. No supervisor is required. The output of the motor map can be used for direct control of an autonomous system in a cluttered environment or for control of the actuators of a biological limb or robot manipulator. The system is able to reach a target even in the presence of an external perturbation. Computer simulations of a point robot and a multi-joint manipulator illustrate the theory.     

A general robot control system for automatic chemical analysis

Advances in instrumentation have led to increasing interest in automatic chemical analyses. Unfortunately, the potential flexibility of robot systems can often not be exploited because of complex programming languages and poor user-interface. These factors generally limit the use of laboratory robots to a few repetitive tasks. This paper describes the development of a general robot control system for automatic chemical analysis. The program is written in Turbo Pascal and Visual Basic and runs in the Microsoft Windows environment. The analytical workspace is designed by selection of an object's icon followed by its desired orientation. Positioning of this object is then performed using a ‘drag and drop’ procedure. The robotic procedure is set-up by selection of items of apparatus and their associated actions. The performance of the system is demonstrated by the determination for caffeine in tablet formulations using a continuous dilution and calibration scheme.     

Self-organised path formation in a swarm of robots

In this paper, we study the problem of exploration and navigation in an unknown environment from an evolutionary swarm robotics perspective. In other words, we search for an efficient exploration and navigation strategy for a swarm of robots, which exploits cooperation and self-organisation to cope with the limited abilities of the individual robots. The task faced by the robots consists in the exploration of an unknown environment in order to find a path between two distant target areas. The collective strategy is synthesised through evolutionary robotics techniques, and is based on the emergence of a dynamic structure formed by the robots moving back and forth between the two target areas. Due to this structure, each robot is able to maintain the right heading and to efficiently navigate between the two areas. The evolved behaviour proved to be effective in finding the shortest path, adaptable to new environmental conditions, scalable to larger groups and larger environment size, and robust to individual failures.     

Information flow principles for plasticity in foraging robot swarms

An important characteristic of a robot swarm that must operate in the real world is the ability to cope with changeable environments by exhibiting behavioural plasticity at the collective level. For example, a swarm of foraging robots should be able to repeatedly reorganise in order to exploit resource deposits that appear intermittently in different locations throughout their environment. In this paper, we report on simulation experiments with homogeneous foraging robot teams and show that analysing swarm behaviour in terms of information flow can help us to identify whether a particular behavioural strategy is likely to exhibit useful swarm plasticity in response to dynamic environments. While it is beneficial to maximise the rate at which robots share information when they make collective decisions in a static environment, plastic swarm behaviour in changeable environments requires regulated information transfer in order to achieve a balance between the exploitation of existing information and exploration leading to acquisition of new information. We give examples of how information flow analysis can help designers to decide on robot control strategies with relevance to a number of applications explored in the swarm robotics literature.     

Emotion Attribution to a Non-Humanoid Robot in Different Social Situations

In the last few years there was an increasing interest in building companion robots that interact in a socially acceptable way with humans. In order to interact in a meaningful way a robot has to convey intentionality and emotions of some sort in order to increase believability. We suggest that human-robot interaction should be considered as a specific form of inter-specific interaction and that human–animal interaction can provide a useful biological model for designing social robots. Dogs can provide a promising biological model since during the domestication process dogs were able to adapt to the human environment and to participate in complex social interactions. In this observational study we propose to design emotionally expressive behaviour of robots using the behaviour of dogs as inspiration and to test these dog-inspired robots with humans in inter-specific context. In two experiments (wizard-of-oz scenarios) we examined humans'' ability to recognize two basic and a secondary emotion expressed by a robot. In Experiment 1 we provided our companion robot with two kinds of emotional behaviour (“happiness” and “fear”), and studied whether people attribute the appropriate emotion to the robot, and interact with it accordingly. In Experiment 2 we investigated whether participants tend to attribute guilty behaviour to a robot in a relevant context by examining whether relying on the robot''s greeting behaviour human participants can detect if the robot transgressed a predetermined rule. Results of Experiment 1 showed that people readily attribute emotions to a social robot and interact with it in accordance with the expressed emotional behaviour. Results of Experiment 2 showed that people are able to recognize if the robot transgressed on the basis of its greeting behaviour. In summary, our findings showed that dog-inspired behaviour is a suitable medium for making people attribute emotional states to a non-humanoid robot.     

Flexible automation of cell culture and tissue engineering tasks

Until now, the predominant use cases of industrial robots have been routine handling tasks in the automotive industry. In biotechnology and tissue engineering, in contrast, only very few tasks have been automated with robots. New developments in robot platform and robot sensor technology, however, make it possible to automate plants that largely depend on human interaction with the production process, e.g., for material and cell culture fluid handling, transportation, operation of equipment, and maintenance. In this paper we present a robot system that lends itself to automating routine tasks in biotechnology but also has the potential to automate other production facilities that are similar in process structure. After motivating the design goals, we describe the system and its operation, illustrate sample runs, and give an assessment of the advantages. We conclude this paper by giving an outlook on possible further developments.     

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Recent research that tests interactive devices for prolonged therapy practice has revealed new prospects for robotics combined with graphical and other forms of biofeedback. Previous human-robot interactive systems have required different software commands to be implemented for each robot leading to unnecessary developmental overhead time each time a new system becomes available. For example, when a haptic/graphic virtual reality environment has been coded for one specific robot to provide haptic feedback, that specific robot would not be able to be traded for another robot without recoding the program. However, recent efforts in the open source community have proposed a wrapper class approach that can elicit nearly identical responses regardless of the robot used. The result can lead researchers across the globe to perform similar experiments using shared code. Therefore modular "switching out"of one robot for another would not affect development time. In this paper, we outline the successful creation and implementation of a wrapper class for one robot into the open-source H3DAPI, which integrates the software commands most commonly used by all robots.     

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N²), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.     

Majority-rule opinion dynamics with differential latency: a mechanism for self-organized collective decision-making

Collective decision-making is a process whereby the members of a group decide on a course of action by consensus. In this paper, we propose a collective decision-making mechanism for robot swarms deployed in scenarios in which robots can choose between two actions that have the same effects but that have different execution times. The proposed mechanism allows a swarm composed of robots with no explicit knowledge about the difference in execution times between the two actions to choose the one with the shorter execution time. We use an opinion formation model that captures important elements of the scenarios in which the proposed mechanism can be used in order to predict the system??s behavior. The model predicts that when the two actions have different average execution times, the swarm chooses with high probability the action with the shorter average execution time. We validate the model??s predictions through a swarm robotics experiment in which robot teams must choose one of two paths of different length that connect two locations. Thanks to the proposed mechanism, a swarm made of robot teams that do not measure time or distance is able to choose the shorter path.     

In Good Company? Perception of Movement Synchrony of a Non-Anthropomorphic Robot

Recent technological developments like cheap sensors and the decreasing costs of computational power have brought the possibility of robotic home companions within reach. In order to be accepted it is vital for these robots to be able to participate meaningfully in social interactions with their users and to make them feel comfortable during these interactions. In this study we investigated how people respond to a situation where a companion robot is watching its user. Specifically, we tested the effect of robotic behaviours that are synchronised with the actions of a human. We evaluated the effects of these behaviours on the robot’s likeability and perceived intelligence using an online video survey. The robot used was Care-O-bot3, a non-anthropomorphic robot with a limited range of expressive motions. We found that even minimal, positively synchronised movements during an object-oriented task were interpreted by participants as engagement and created a positive disposition towards the robot. However, even negatively synchronised movements of the robot led to more positive perceptions of the robot, as compared to a robot that does not move at all. The results emphasise a) the powerful role that robot movements in general can have on participants’ perception of the robot, and b) that synchronisation of body movements can be a powerful means to enhance the positive attitude towards a non-anthropomorphic robot.     

Low impedance walking robots

For both historical and technological reasons, most robots,including those meant to mimic animals or operate in naturalenvironments,³ use actuators and control systems that have high(stiff) mechanical impedance. By contrast, most animals exhibitlow (soft) impedance. While a robot's stiff joints may be programmedto closely imitate the recorded motion of an animal's soft joints,any unexpected position disturbances will generate reactiveforces and torques much higher for the robot than for the animal.The dual of this is also true: while an animal will react toa force disturbance by significantly yielding position, a typicalrobot will greatly resist. These differences cause three deleterious effects for high impedancerobots. First, the higher forces may cause damage to the robotor to its environment (which is particularly important if thatenvironment includes people). Second, the robot must acquirevery precise information about its position relative to theenvironment so as to minimize its velocity upon impact. Third,many of the self-stabilizing effects of natural dynamics are"shorted out"⁴ by the robot's high impedance, so that stabilizationrequires more effort from the control system. Over the past 5 yr, our laboratory has designed a series ofwalking robots based on "Series-Elastic Actuators" and "VirtualModel Control." Using these two techniques, we have been ableto build low-impedance walking robots that are both safe androbust, that operate blindly without any model of upcoming terrain,and that add minimal control effort in parallel to their self-stabilizingpassive dynamics. We have discovered that it is possible toachieve surprisingly effective ambulation from rather simplemechanisms and control systems. After describing the historicaland technological motivations for our approach, this paper givesan overview of our methods and shows some of the results wehave obtained.     

Self-organized flocking in mobile robot swarms

In this paper, we study self-organized flocking in a swarm of mobile robots. We present Kobot, a mobile robot platform developed specifically for swarm robotic studies. We describe its infrared-based short range sensing system, capable of measuring the distance from obstacles and detecting kin robots, and a novel sensing system called the virtual heading system (VHS) which uses a digital compass and a wireless communication module for sensing the relative headings of neighboring robots. We propose a behavior based on heading alignment and proximal control that is capable of generating self-organized flocking in a swarm of Kobots. By self-organized flocking we mean that a swarm of mobile robots, initially connected via proximal sensing, is able to wander in an environment by moving as a coherent group in open space and to avoid obstacles as if it were a “super-organism”. We propose a number of metrics to evaluate the quality of flocking. We use a default set of behavioral parameter values that can generate acceptable flocking in robots, and analyze the sensitivity of the flocking behavior against changes in each of the parameters using the metrics that were proposed. We show that the proposed behavior can generate flocking in a small group of physical robots in a closed arena as well as in a swarm of 1000 simulated robots in open space. We vary the three main characteristics of the VHS, namely: (1) the amount and nature of noise in the measurement of heading, (2) the number of VHS neighbors, and (3) the range of wireless communication. Our experiments show that the range of communication is the main factor that determines the maximum number of robots that can flock together and that the behavior is highly robust against the other two VHS characteristics. We conclude by discussing this result in the light of related theoretical studies in statistical physics.     

A Switching Controller System for a Wheeled Mobile Robot

A wheeled mobile mechanism with a passive and/or active linkage mechanism for rough terrain environment is developed and evaluated. The wheeled mobile mechanism which has high mobility in rough terrain needs sophisticated system to adapt various environments.We focus on the development of a switching controller system for wheeled mobile robots in rough terrain. This system consists of two sub-systems: an environment recognition system using link angles and an adaptive control system. In the environment recognition system, we introduce a Self-Organizing Map (SOM) for clustering link angles. In the adaptive controllers, we introduce neural networks to calculate the inverse model of the wheeled mobile robot.The environment recognition system can recognize the environment in which the robot travels, and the adjustable controllers are tuned by experimental results for each environment. The dual sub-system switching controller system is experimentally evaluated. The system recognizes its environment and adapts by switching the adjustable controllers. This system demonstrates superior performance to a well-tuned single PID controller.     

Perception of Graphical Virtual Environments by Blind Users via Sensory Substitution

Graphical virtual environments are currently far from accessible to blind users as their content is mostly visual. This is especially unfortunate as these environments hold great potential for this population for purposes such as safe orientation, education, and entertainment. Previous tools have increased accessibility but there is still a long way to go. Visual-to-audio Sensory-Substitution-Devices (SSDs) can increase accessibility generically by sonifying on-screen content regardless of the specific environment and offer increased accessibility without the use of expensive dedicated peripherals like electrode/vibrator arrays. Using SSDs virtually utilizes similar skills as when using them in the real world, enabling both training on the device and training on environments virtually before real-world visits. This could enable more complex, standardized and autonomous SSD training and new insights into multisensory interaction and the visually-deprived brain. However, whether congenitally blind users, who have never experienced virtual environments, will be able to use this information for successful perception and interaction within them is currently unclear.We tested this using the EyeMusic SSD, which conveys whole-scene visual information, to perform virtual tasks otherwise impossible without vision. Congenitally blind users had to navigate virtual environments and find doors, differentiate between them based on their features (Experiment1:task1) and surroundings (Experiment1:task2) and walk through them; these tasks were accomplished with a 95% and 97% success rate, respectively. We further explored the reactions of congenitally blind users during their first interaction with a more complex virtual environment than in the previous tasks–walking down a virtual street, recognizing different features of houses and trees, navigating to cross-walks, etc. Users reacted enthusiastically and reported feeling immersed within the environment. They highlighted the potential usefulness of such environments for understanding what visual scenes are supposed to look like and their potential for complex training and suggested many future environments they wished to experience.     

基于高性能服务器及网格技术的生物科研服务平台研究

为了解决生物科学方面的研究人员在使用生物研究软件工具中存在的“不知道、选不出、难学习和用不起”等问题,同时也为了能为生物类院校的师生提供教学辅助,利用网格技术在高性能服务器上,建立了一款服务于生物研究和教学的网上生物科研服务平台（Biological study service platform,BSP）。该平台包含“工具大全、工具论坛和web工作台”等三部分,拟分别从“找,学,用”三个方面彻底解决生物研究人员在使用生物研究软件工具中存在的问题,同时也为生物类的教师和学生提供了教与学平台。访问地址如下：http：//218．57．145．30：9999／biosp／。此外,该研究小组还将不断地更新和改进该平台,开发更多的自主应用软件,更好地服务生物科研工作。