Microscale and nanoscale robotics systems [Grand Challenges of Robotics]

Depending on their overall size, sensing and actuation precision, part or tool size, and task space, robotic systems can be classified as microrobotics or nanorobotics, respectively. Micro/nanorobotics represents these two different scale robotics areas jointly while keeping their clear scale differences in mind. At its current early infancy, the field of micro/nanorobotics has two major research thrust areas. Analogous to the manipulation area in macroscale robotics, the first area explores new methods for programmable manipulation and assembly of micro- and nanoscale entities. Here, the overall micro/nanorobotic system size can be very large, while only the manipulation tools, manipulated objects, and sensing, actuation, and manipulation precision are required to be at the micro/nanoscale. On the other hand, the second research area focuses on overall miniaturization of mobile robots down to mum overall sizes with various locomotion capabilities such as flying, swimming, walking, hopping, rolling, and climbing. In these mobile robotic systems, overall system size is very limited, which induces severe constraints in utilized actuators, sensors, motion mechanisms, power sources, computing power, and wireless communication capability. These two research thrusts are described in detail in the following sections     

Rescue robotics — a crucial milestone on the road to autonomous systems

Rescue robotics is an important steppingstone in the scientific challenge to create autonomous systems. There is a significant market for rescue robots, which have unique features that allow a fruitful combination of application-oriented developments and basic research. Unlike other markets for advanced robotics systems like service robots, the rescue robotics domain benefits from the fact that there is a human in the loop, which allows a stepwise transition from dumb teleoperated devices to truly autonomous systems. Current teleoperated devices are already very useful in this domain and they benefit from any bit of autonomy added. Human rescue workers are a scarce resource at disaster scenarios. A single operator should, hence, ideally supervise a multitude of robots. We present results from the rescue robots at the International University Bremen in a core area supporting autonomy, i.e., mapping.     

Adaptive navigation for autonomous robots

In many robotic exploration missions, robots have to learn specific policies that allow them to: (i) select high level goals (e.g., identify specific destinations), (ii) navigate (reach those destinations), (iii) and adapt to their environment (e.g., modify their behavior based on changing environmental conditions). Furthermore, those policies must be robust to signal noise or unexpected situations, scalable to more complex environments, and account for the physical limitations of the robots (e.g., limited battery power and computational power).In this paper we evaluate reactive and learning navigation algorithms for exploration robots that must avoid obstacles and reach specific destinations in limited time and with limited observations. Our results show that neuro-evolutionary algorithms with well-designed evaluation functions can produce up to 50% better performance than reactive algorithms in complex domains where the robot’s goals are to select paths that lead to seek specific destinations while avoiding obstacles, particularly when facing significant sensor and actuator signal noise.     

Prediction of Human Behavior in Human--Robot Interaction Using Psychological Scales for Anxiety and Negative Attitudes Toward Robots

When people interact with communication robots in daily life, their attitudes and emotions toward the robots affect their behavior. From the perspective of robotics design, we need to investigate the influences of these attitudes and emotions on human-robot interaction. This paper reports our empirical study on the relationships between people's attitudes and emotions, and their behavior toward a robot. In particular, we focused on negative attitudes, anxiety, and communication avoidance behavior, which have important implications for robotics design. For this purpose, we used two psychological scales that we had developed: negative attitudes toward robots scale (NARS) and robot anxiety scale (RAS). In the experiment, subjects and a humanoid robot are engaged in simple interactions including scenes of meeting, greeting, self-disclosure, and physical contact. Experimental results indicated that there is a relationship between negative attitudes and emotions, and communication avoidance behavior. A gender effect was also suggested.     

Active compliant motion: a survey

Whether they are asked to polish or assemble parts, clean the house or open doors, the future generation of robots will have to cope with contact tasks under uncertainty in a stable and safe manner. Obtaining a controlled contact motion under uncertainty is still a major challenge for the robotics community. At present most research groups focus on one of the subcomponents (i.e., modeling, planning, estimation or control) of the system, and no overall system is developed yet. This paper presents a literature survey of the state-of-the-art of the subcomponents and points to the need for effective integration of those components.     

A MEMS nano-extensometer with integrated de-amplification mechanism

Experimental exploration of strained nanostructures, such as nanowires and bio-molecules, is essential for understanding their properties. However, the ability to apply and to quantify nanometer displacements is challenging. We present a novel MEMS nano-extensometer with integrated actuation and compliant de-amplification mechanism allowing the accurate characterization of stretched nanostructures. A feasibility study was followed by fabrication and characterization of the device. The de-amplified displacement was registered via optical microscopy and was processed using an improved digital image correlation algorithm to achieve nanometer measurement accuracy. Using our technique, nanoscale displacement can be determined by means of simple imaging tools. This was demonstrated by stretching suspended single wall carbon nanotubes.     

Understanding and Reconstruction of the Mobiligence of Insects Employing Multiscale Biological Approaches and Robotics

Adaptability, i.e., the ability to behave in accordance with a ceaselessly changing environment, is a defining feature of animals, including insects, and is a necessary attribute in robotics. Insects display a range of sophisticated behaviors in response to their environments based on the processing of a simple nervous system. Insects are uniquely suited for multidisciplinary studies of the brain involving a combined approach at several levels, from molecules and single neurons to neural networks and behavior. Furthermore, insects can be adapted for use with a wide variety of methodological approaches, from molecular genetics, electrophysiology and imaging to computational tools and robotics. Thus, insects are an excellent model taxon for understanding adaptive control in biological systems. In this review, the general features of the insect brain and multiscale approaches for understanding the neural basis of their behavior are introduced. As an example of adaptive behavior in insects, odor–source orientation behavior in silkmoths and the feasibility of a behavioral strategy based on their neural system, with implementation in robots, is described. Finally, we present novel approaches using an insect–machine hybrid, which will enhance our ability to evaluate and understand adaptive behavior.     

Soft Robotics: Morphology and Morphology-inspired Motion Strategy

Robotics has aroused huge attention since the 1950s. Irrespective of the uniqueness that industrial applications exhibit, conventional rigid robots have displayed noticeable limitations, particularly in safe cooperation as well as with environmental adaption. Accordingly, scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured environments. For decades, they have been committed to exploring sub-fields of soft robotics (e.g., cutting-edge techniques in design and fabrication, accurate modeling, as well as advanced control algorithms). Although scientists have made many different efforts, they share the common goal of enhancing applicability. The presented paper aims to brief the progress of soft robotic research for readers interested in this field, and clarify how an appropriate control algorithm can be produced for soft robots with specific morphologies. This paper, instead of enumerating existing modeling or control methods of a certain soft robot prototype, interprets for the relationship between morphology and morphology-dependent motion strategy, attempts to delve into the common issues in a particular class of soft robots, and elucidates a generic solution to enhance their performance.      

Exploring the design space of robots: Children''s perspectives

Children's perceptions and evaluations of different robot designs are an important unexplored area within robotics research considering that many robots are specifically designed for children. To examine children's feelings and attitudes towards robots, a large sample of children (N = 159) evaluated 40 robot images by completing a questionnaire for each image, which enquired about robot appearance, robot personality dimensions and robot emotions. Results showed that depending on a robot's appearance children clearly distinguished robots in terms of their intentions (i.e. friendly vs. unfriendly), their capability to understand, and their emotional expression. Results of a principal components analysis of the children's ratings of the robots' personality attributes revealed two dimensions labelled ‘Behavioural Intention’ and ‘Emotional Expression’. Robots were classified according to their scores on these two dimensions and a content analysis of their appearance was conducted in an attempt to identify salient features of different robot personalities. Children judged human-like robots as aggressive, but human–machine robots as friendly. Results on children's perceptions of the robots' behavioural intentions provided tentative empirical support for the Uncanny Valley, hypothesized by (Mori, M., 1970), reflecting a situation where robots are very human-like, but still distinguishable from humans, evoking a feeling of discomfort or repulsion. The paper concludes with a discussion of design implications for robots, and the use of robots in educational contexts.     

Self-assembly and self-repair of arbitrary shapes by a swarm of reactive robots: algorithms and simulations

Self-assembly of active, robotic agents, rather than of passive agents such as molecules, is an emerging research field that is attracting increasing attention. Active self-assembly techniques are especially attractive at very small spatial scales, where alternative construction methods are unavailable or have severe limitations. Building nanostructures by using swarms of very simple nanorobots is a promising approach for manufacturing nanoscale devices and systems. The method described in this paper allows a group of simple, physically identical, identically programmed and reactive (i.e., stateless) agents to construct and repair polygonal approximations to arbitrary structures in the plane. The distributed algorithms presented here are tolerant of robot failures and of externally-induced disturbances. The structures are self-healing, and self-replicating in a weak sense. Their components can be re-used once the structures are no longer needed. A specification of vertices at relative positions, and the edges between them, is translated by a compiler into reactive rules for assembly agents. These rules lead to the construction and repair of the specified shape. Simulation results are presented, which validate the proposed algorithms.     

Strengths and synergies of evolved and designed controllers: A study within collective robotics

This paper analyses the strengths and weaknesses of self-organising approaches, such as evolutionary robotics, and direct design approaches, such as behaviour-based controllers, for the production of autonomous robots' controllers, and shows how the two approaches can be usefully combined. In particular, the paper proposes a method for encoding evolved neural-network based behaviours into motor schema-based controllers and then shows how these controllers can be modified and combined to produce robots capable of solving new tasks. The method has been validated in the context of a collective robotics scenario in which a group of physically assembled simulated autonomous robots are requested to produce different forms of coordinated behaviours (e.g., coordinated motion, walled-arena exiting, and light pursuing).     

Robot accuracy and stiffness—An experimental study

Investigations in robotics have been mainly directed toward the design of robots with a significant degress of intelligence, capable of high adaptability. However, very little research has been done on the design of a robot manipulator as an executive mechanism of the intelligent control system, whose high quality design will allow the sophisticated functions imposed by the control system.

Experimental investigations of robot accuracy show unacceptable results which limit their future wider application. This is the reason why the off-life programming of robots has not been widely used, without which it is impossible to imagine a more significant integrationof robots in the CIM environment.

The object of our study has been to find out the causes of low degreee of robot accuracy, emphasizing the non-corresponding choice of the robot coordinate system, algorithmic and computational errors and drive and transmission element design. Comparison with corresponding results gained from investigations of CNC machine tools cannot be avoided because of the fact that robots are also machines from which accuracy is required. What is missing in robotics today, but which inevitably is required, is the establishment of a standard methodology for testing robot accuracy and other performance.     

Advances in robotics (Review)

The state and prospects of macro-, micro-, and nanorobotics are described. The role of industrial robots in the creation of modern automated production is shown. Developments in the field of mobile robots and examples of their use are given. Miniaturization and molecular manufacturing are addressed as two approaches to nanorobot development.     

An Oscillator Model That Enables Motion Stabilization and Motion Exploration by Exploiting Multi-Rhythmicity

Central pattern generators (CPGs) have been increasingly attracting the attention of roboticists in the hope that they will enable robots to realize truly supple and agile locomotion under real-world constraints. Thus far, various CPG models have been proposed, particularly in terms of motion stabilization against external perturbations (i.e., limit cycle behavior). On the other hand, biological CPGs have another crucial aspect that cannot be neglected (i.e., motion exploration). Here, note that motion stabilization and motion exploration should be performed in different time-scales. Now the following questions arise: 'How can different time-scales be embedded into a single CPG effectively?' and 'What is a good mathematical tool for describing the coexistence of different time-scales?'. To overcome these problems, this paper introduces a novel oscillator model in which the two functions of motion stabilization and motion exploration can be seamlessly integrated by exploiting the concept of multi-rhythmicity, without relying on any hierarchical structure (e.g., Higher Center), which in turn enables that learning is the time evolution of a dynamical system (motor control system) that integrates motion exploration with motion stabilization. We applied this model to the learning of hopping motion as a practical example. Simulation and experimental results indicate that the robot can successfully perform online learning without the need for a separation between learning and performance phases.     

Multi-robot exploration under the constraints of wireless networking

A multi-robot system can be highly beneficial for exploration, which is a core robotics task. Application domains include, for example, surveillance, reconnaissance, planetary exploration or rescue missions. When using a team of robots, the overall performance can be much faster and more robust. In this article, an approach to multi-robot exploration is presented that takes the constraints of wireless networking into account. An algorithm is introduced based on a population that samples the possible moves of all robots and a utility to select the best one in each time step. Results from two scenarios are presented. In the first one, a team of robots explores its environment while permanently maintaining an ad hoc network structure with each other as well as a base station at a fixed location. In the second one, the robots move freely as a pack while maintaining communication with each other.     

Challenges and future trends in marine robotics

Spawned by fast paced progress in marine science and technology, the past two decades have witnessed growing interest in ocean exploration and exploitation for scientific and commercial purposes, the development of technological products for the maritime and offshore industries, and a host of other activities in which the marine environment takes center stage. In this context, marine robotics has steadily emerged as a key enabling technology for the execution of increasingly complex and challenging missions at sea. Intensive research and development in this field have led to major advances and shown unequivocally the effectiveness and reliability of marine robotics solutions in several domains. This progress goes hand in hand with the availability of increasingly sophisticated acoustic networks for multiple, cooperative missions involving surface and underwater robots. At the root of this trend is the fruitful dialogue between robotic systems developers and end-users with the capacity to convert general mission objectives into functional and technical specifications that serve as application-driven requirements for engineering development. The result is the tremendous progress observed in the consolidated methodologies and procedures adopted and the consequent impact on science, industry, and the society at large. In spite of the progress in the area, however many challenges must still be faced and novel applications will continue to set further requirements for future generations of marine robots and their enabling systems. The time is therefore appropriate to overview recent trends in the field of marine robotics and assess their impact on several important application domains. With these objectives in mind, in the present paper we highlight key technological achievements in the field, analyze some of the shortcomings encountered, and indicate specific issues that warrant further research and development effort. To this end, we review a number of highly representative projects in the field, with due account for the theoretical frameworks upon which technological developments build upon. Finally, the paper concludes with an outlook on the future of marine robotics, both from a theoretical and practical standpoint, and describes recently initiated projects that hold promise for the development of advanced tools and systems for ocean exploration and exploitation.     

Worker selection of safe speed and idle condition in simulated monitoring of two industrial robots

Industrial robots often operate at high speed, with unpredictable motion patterns and erratic idle times. Serious injuries and deaths have occurred due to operator misperception of these robot design and performance characteristics. The main objective of the research project was to study human perceptual aspects of hazardous robotics workstations. Two laboratory experiments were designed to investigate workers' perceptions of two industrial robots with different physical configurations and performance capabilities. Twenty-four subjects participated in the study. All subjects were chosen from local industries, and had had considerable exposure to robots and other automated equipment in their working experience. Experiment 1 investigated the maximum speed of robot arm motions that workers, who were experienced with operation of industrial robots, judged to be 'safe' for monitoring tasks. It was found that the selection of safe speed depends on the size of the robot and the speed with which the robot begins its operation. Speeds of less than 51 cm/s and 63 cm/s for large and small robots, respectively, were perceived as safe, i.e., ones that did not result in workers feeling uneasy or endangered when working in close proximity to the robot and monitoring its actions. Experiment 2 investigated the minimum value of robot idle time (inactivity) perceived by industrial workers as system malfunction, and an indication of the 'safe-to-approach' condition. It was found that idle times of 41 s and 28 s or less for the small and large robots, respectively, were perceived by workers to be a result of system malfunction. About 20% of the workers waited only 10 s or less before deciding that the robot had stopped because of system malfunction. The idle times were affected by the subjects' prior exposure to a simulated robot accident. Further interpretations of the results and suggestions for operational limitations of robot systems are discussed.     

Wavelet-based feature extraction using probabilistic finite state automata for pattern classification

Real-time data-driven pattern classification requires extraction of relevant features from the observed time series as low-dimensional and yet information-rich representations of the underlying dynamics. These low-dimensional features facilitate in situ decision-making in diverse applications, such as computer vision, structural health monitoring, and robotics. Wavelet transforms of time series have been widely used for feature extraction owing to their time-frequency localization properties. In this regard, this paper presents a symbolic dynamics-based method to model surface images, generated by wavelet coefficients in the scale-shift space. These symbolic dynamics-based models (e.g., probabilistic finite state automata (PFSA)) capture the relevant information, embedded in the sensor data, from the associated Perron-Frobenius operators (i.e., the state-transition probability matrices). The proposed method of pattern classification has been experimentally validated on laboratory apparatuses for two different applications: (i) early detection of evolving damage in polycrystalline alloy structures, and (ii) classification of mobile robots and their motion profiles.     

康复辅助机器人及其物理人机交互方法

面对中国社会快速老龄化现状和庞大的残疾人群,康复辅助机器人研究具有重要学术价值和广阔的应用前景.康复辅助机器人研究涉及神经科学、生物力学、机器人自动控制等领域知识,是机器人最具挑战性和最受关注的研究领域之一.与其他机器人不同,康复辅助机器人的作用对象是人,存在人与机器人的信息交流和能量交换,物理人机交互控制方法是其研究核心和关键技术.本文以神经康复机器人、穿戴式外骨骼、智能假肢等应用为例,介绍当前的研究现状,并重点介绍人体运动意图识别方法和交互控制方法等研究重点和难点.最后展望该领域的未来技术发展方向.