基于高仿生形态布局的仿鸽扑翼飞行机器人系统设计

针对现有扑翼飞行机器人存在的飞行形态与实际鸟类相差较大, 以及翅膀、尾翼布局和俯仰、转向控制方式仿生度较低的问题, 提出一种形态布局与鸽子相仿的扑翼飞行机器人系统设计及实现方案. 通过设计弧面−折翼−后掠翅膀、仿鸟扇形尾翼以及尾翼挨近翅膀后缘布置的布局方式, 使扑翼机器人飞行形态更加接近真实鸟类, 提高扑翼机器人的形态仿生度. 在此基础上, 设计结合下扑角调控无需尾翼大角度上翘的俯仰控制方式, 以及不依赖于尾翼的翅膀收缩转向控制方式, 在提高仿生度的同时保证飞行控制的有效性. 在具体设计过程中, 首先参考鸽子翅膀型式选择不同类型翅膀并进行风洞测试, 确定出下扑角变化时仍能保持较优升推力性能的翅膀设计方案; 其次, 对各种尾翼型式进行分析和比较, 结合鸽子尾翼特点进行仿鸽尾翼及俯仰、转向控制机构设计, 并通过风洞测试验证; 最后, 设计飞控系统并装配整机, 进行外场飞行测试, 验证仿鸽扑翼飞行机器人平台的稳定性和可控性.     

Passive torque regulation in an underactuated flapping wing robotic insect

Recent developments in millimeter-scale fabrication processes have led to rapid progress towards creating airborne flapping wing robots based on Dipteran (two winged) insects. Previous work to regulate forces and torques generated by flapping wings has focused on controlling wing trajectory. An alternative approach uses underactuated mechanisms with tuned dynamics to passively regulate these forces and torques. The resulting ??mechanically intelligent?? devices execute wing trajectory corrections to realize desired body forces and torques without the intervention of an active controller. This article describes an insect-scale flapping wing mechanism consisting of a single piezoelectric actuator, an underactuated transmission, and passively rotating wings. Wing stroke velocities are passively modulated to eliminate net airframe roll torque. A theoretical model predicts lift generating wing trajectories and quantifies the passive reduction in roll torque. An experimental structure provides an at-scale demonstration of passive torque regulation.     

Dissection of a Flexible Wing's Performance for Insect-Inspired Flapping-Wing Micro Air Vehicles

We present a computational study on the aerodynamic performance of flexible wings aiming to facilitate the design of insect-inspired flapping-wing micro air vehicles (FMAVs). First, we propose using a two-dimensional mechanical model for a flapping wing to help understand the mechanism underlying its unsteady deformation when exposed to aerodynamic and inertia forces. This is followed by comparative analyses of both flexible wings and fixed wings in flight. In particular, a 'swaying propulsion' mechanism is proposed to mimic the flapping of the winged insects, and a new concept of 'initial torsion angle' is introduced to provide an equivalent means to account for the asymmetry of the torsional stiffness of the thorax muscle during upstroke and downstroke flapping. Subsequently, the aerodynamic forces and power requirements for a bumblebee's wings under various flight conditions are systematically examined. Our results indicate that flexibility of the wings largely contributes to the high lifts and that gliding forces play a significant role in improving flight performance, suggesting that optimal design of the structure and flapping motions of wings could achieve improved efficiency in FMAVs. These studies promote a brand new design concept for future insect-inspired FMAVs.     

Adaptable compliance or variable stiffness for robotic applications [From the Guest Editors]

Exciting new robots are being developed that will operate in a different environment from traditional industrial factories or research laboratories. Researchers are working worldwide to create robots that are integrated into our daily lives. For the advancement of these new robots, compliant, safe, and new actuators are one of the important issues turning energy into safe motion. The biological counterpart is the muscle tendon structure that has functional performance characteristics and a neuromechanical control systemthat has far more superior capabilities. The superior power to weight ratio, force to weight ratio, and sensing characteristics limit the development of machines that can match motion, safety, and energy efficiency of a human or other animal. One of the key differences of biological systems is their adaptable compliance or variable stiffness compared with the traditional stiff electrical drives used for the standard industrial robotic applications, which require accurate, reference-trajectory tracking.More and more applications such as robots in close human or robot proximity, legged autonomous robots, and rehabilitation devices and prostheses demand a different set of design specifications, for which the use of compliant actuators can be beneficial as compared with the traditional stiff actuation schemes.     

Development of a Flying Robot With a Pantograph-Based Variable Wing Mechanism

We develop a flying robot with a new pantograph-based variable wing mechanism for horizontal-axis rotorcrafts (cyclogyro rotorcrafts). A key feature of the new mechanism is to have a unique trajectory of variable wings that not only change angles of attack but also expand and contract according to wing positions. As a first step, this paper focuses on demonstrating the possibility of the flying robot with this mechanism. After addressing the pantograph-based variable wing mechanism and its features, a simulation model of this mechanism is constructed. Next, we present some comparison results (between the simulation model and experimental data) for a prototype body with the proposed pantograph-based variable wing mechanism. Both simulation and experimental results show that the flying robot with this new mechanism can generate enough lift forces to keep itself in the air. Furthermore, we construct a more precise simulation model by considering rotational motion of each wing. As a result of optimizing design parameters using the precise simulation model, flight performance experimental results demonstrate that the robot with the optimal design parameters can generate not only enough lift forces but a 155 gf payload as well.      

Present and future robot control development—An industrial perspective

Robot control is a key competence for robot manufacturers and a lot of development is made to increase robot performance, reduce robot cost and introduce new functionalities. Examples of development areas that get big attention today are multi robot control, safe control, force control, 3D vision, remote robot supervision and wireless communication. The application benefits from these developments are discussed as well as the technical challenges that the robot manufacturers meet. Model-based control is now a key technology for the control of industrial robots and models and control schemes are continuously refined to meet the requirements on higher performance even when the cost pressure leads to the design of robot mechanics that is more difficult to control. Driving forces for the future development of robots can be found in, for example, new robot applications in the automotive industry, especially for the final assembly, in small and medium size enterprises, in foundries, in food industry and in the processing and assembly of large structures. Some scenarios on future robot control development are proposed. One scenario is that light-weight robot concepts could have an impact on future car manufacturing and on future automation of small and medium size enterprises (SMEs). Such a development could result in modular robots and in control schemes using sensors in the robot arm structure, sensors that could also be used for the implementation of redundant safe control. Introducing highly modular robots will increase the need of robot installation support, making Plug and Play functionality even more important. One possibility to obtain a highly modular robot program could be to use a recently developed new type of parallel kinematic robot structure with large work space in relation to the robot foot print. For further efficient use of robots, the scenario of adaptive robot performance is introduced. This means that the robot control is optimised with respect to the thermal and fatigue load on the robot for the specific program that the robot performs. The main conclusion of the presentation is that industrial robot development is far away from its limits and that a lot of research and development is needed to obtain a more widely use of robot automation in industry.     

A Novel Amphibious Spherical Robot Equipped with Flywheel,Pendulum, and Propeller

The ability of amphibious movement is found widely among small animals such as frogs, tortoises, snakes, and crabs. They can move on land, in water, and even on the water bottom. Inspired by the animals’ moving capability, an amphibious spherical robot with flywheel, pendulum, and propeller has been developed. In this paper, the mechanical structure, motion performance, control architecture, and experimentation of the amphibious spherical robot are presented. The robot can show three outstanding advantages for underwater observation, which distinguish it from the other existing observing robots. First, it can resist great water pressure to protect the internal components that is based on the spherical shell. Second, the robot only requires a single propeller to achieve the flexible movement and control posture in water. Third, the robot can roll on land or on water bottom only through an internal motor that can reduce the energy consumption during the observation process. The robot has a wide range of applications such as underwater observation, search and rescue, sensor networks.     

Maze exploration behaviors using an integrated evolutionary robotics environment

This paper presents results generated with a new evolutionary robotics (ER) simulation environment and its complementary real mobile robot colony research test-bed. Neural controllers producing mobile robot maze searching and exploration behaviors using binary tactile sensors as inputs were evolved in a simulated environment and subsequently transferred to and tested on real robots in a physical environment. There has been a considerable amount of proof-of-concept and demonstration research done in the field of ER control in recent years, most of which has focused on elementary behaviors such as object avoidance and homing. Artificial neural networks (ANN) are the most commonly used evolvable controller paradigm found in current ER literature. Much of the research reported to date has been restricted to the implementation of very simple behaviors using small ANN controllers. In order to move beyond the proof-of-concept stage our ER research was designed to train larger more complicated ANN controllers, and to implement those controllers on real robots quickly and efficiently. To achieve this a physical robot test-bed that includes a colony of eight real robots with advanced computing and communication abilities was designed and built. The real robot platform has been coupled to a simulation environment that facilitates the direct wireless transfer of evolved neural controllers from simulation to real robots (and vice versa). We believe that it is the simultaneous development of ER computing systems in both the simulated and the physical worlds that will produce advances in mobile robot colony research. Our simulation and training environment development focuses on the definition and training of our new class of ANNs, networks that include multiple hidden layers, and time-delayed and recurrent connections. Our physical mobile robot design focuses on maximizing computing and communications power while minimizing robot size, weight, and energy usage. The simulation and ANN-evolution environment was developed using MATLAB. To allow for efficient control software portability our physical evolutionary robots (EvBots) are equipped with a PC-104-based computer running a custom distribution of Linux and connected to the Internet via a wireless network connection. In addition to other high-level computing applications, the mobile robots run a condensed version of MATLAB, enabling ANN controllers evolved in simulation to be transferred directly onto physical robots without any alteration to the code. This is the first paper in a series to be published cataloging our results in this field.     

Transferring knowledge across robots: A risk sensitive approach

One of the most impressive characteristics of human perception is its domain adaptation capability. Humans can recognize objects and places simply by transferring knowledge from their past experience. Inspired by that, current research in robotics is addressing a great challenge: building robots able to sense and interpret the surrounding world by reusing information previously collected, gathered by other robots or obtained from the web. But, how can a robot automatically understand what is useful among a large amount of information and perform knowledge transfer? In this paper we address the domain adaptation problem in the context of visual place recognition. We consider the scenario where a robot equipped with a monocular camera explores a new environment. In this situation traditional approaches based on supervised learning perform poorly, as no annotated data are provided in the new environment and the models learned from data collected in other places are inappropriate due to the large variability of visual information. To overcome these problems we introduce a novel transfer learning approach. With our algorithm the robot is given only some training data (annotated images collected in different environments by other robots) and is able to decide whether, and how much, this knowledge is useful in the current scenario. At the base of our approach there is a transfer risk measure which quantifies the similarity between the given and the new visual data. To improve the performance, we also extend our framework to take into account multiple visual cues. Our experiments on three publicly available datasets demonstrate the effectiveness of the proposed approach.     

Semi-autonomous serially connected multi-crawler robot for search and rescue

In this paper, we develop a semi-autonomous serially connected multi-crawler robot for search and rescue. In large-scale disasters, such as earthquakes and tornadoes, the application of rescue robots to search for survivors under rubble would be beneficial. Snake-like robots (robots composed of serially connected units) are an effective candidate for such robots. Their long body enables them to overcome obstacles, and they can move into narrow spaces because of their thin shape. However, conventional snake-like robots have significant problems with operability. The numerous degrees of freedom of their bodies require complex operation to overcome obstacles, and training is required for the operators. Thus, survivors or community members cannot operate conventional robots to search for victims, despite the availability of such rescue robots. Here, we address this problem and develop a semi-autonomous serially connected multi-crawler robot designed for non-trained operators, such as community members or rescued survivors. It can be controlled easily by a conventional two-channel user interface with levers for turning and straight line motion. To demonstrate the effectiveness of our proposed mechanism, a prototype robot was developed and experiments were conducted. The results confirm that the proposed robot had both higher operability and higher mobility than conventional robots.     

Energy-optimal gait analysis of quadruped robots

It is important for walking robots such as quadruped robots to have an efficient gait. Since animals and insects are the basic models for most walking robots, their walking patterns are good examples. In this study, the walking energy consumption of a quadruped robot is analyzed and compared with natural animal gaits. Genetic algorithms have been applied to obtain the energy-optimal gait when the quadruped robot is walking with a set velocity. In this method, an individual in a population represents the walking pattern of the quadruped robot. The gait (individual) which consumes the least energy is considered to be the best gait (individual) in this study. The energy-optimal gait is analyzed at several walking velocities, since the amount of walking energy consumption changes if the walking velocity of the robot is changed. The results of this study can be used to decide what type of gait should be generated for a quadruped robot as its walking velocity changes. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001.     

Toward Mission Capable Legged Robots through Biological Inspiration

Insects provide good models for the design and control of mission capable legged robots. We are using intelligent biological inspiration to extract the features important for locomotion from insect neuromechanical designs and implement them into legged robots. Each new model in our series of robots represents an advance in agility, strength, or energy efficiency, which are all important for performing missions. Robot IV is being constructed with a cockroach mechanical design. It features a lightweight exoskeleton structure and McKibben artificial muscles for passive joint stiffness. Our self-contained microrobot has rear legs that are inspired by cricket. Its diminutive size required us to custom fabricate almost all of its parts, including its McKibben actuators.     

Multi-rigid-body dynamics and online model predictive control for transformable multi-links aerial robot*

Transformable multi-links aerial robots have great potentials in application relying on the transformable features to change its shape during the flight. Compared to traditional quadrotor robots, transformable multi-links robots are equipped with servo motor between links. To simplify the non-linear dynamic system, the previous work restricts the robot to transform in very slow speed so that the robot could be approximated as a quadrotor robot at each time point. However, tradeoff comes as the dynamic performance is given up. In this paper, we come up with a new framework combining of computationally efficient non-linear model predictive controller and motion primitive to optimize thrust force and joints trajectory of the multi-links aerial robot. Finally, we verify our framework with fast transformation motions and table tennis task which requires dynamic performance.     

A Bio-Inspired Flapping-Wing Robot With Cambered Wings and Its Application in Autonomous Airdrop

Flapping-wing flight, as the distinctive flight method retained by natural flying creatures, contains profound aerodynamic principles and brings great inspirations and encouragements to drone developers. Though some ingenious flapping-wing robots have been designed during the past two decades, development and application of autonomous flapping-wing robots are less successful and still require further research. Here, we report the development of a servo-driven bird-like flapping-wing robot named USTBird-I and its application in autonomous airdrop. Inspired by birds, a camber structure and a dihedral angle adjustment mechanism are introduced into the airfoil design and motion control of the wings, respectively. Computational fluid dynamics simulations and actual flight tests show that this bionic design can significantly improve the gliding performance of the robot, which is beneficial to the execution of the airdrop mission. Finally, a vision-based airdrop experiment has been successfully implemented on USTBird-I, which is the first demonstration of a bird-like flapping-wing robot conducting an outdoor airdrop mission.      

Fault detection for service mobile robots using model-based method

Detection of faults is a topic of high importance because it increases robot dependability, a requirement for the wide acceptance of service robots in domestic environments. This work takes a model-based approach for detecting and identifying actuator faults on differential-drive mobile robots in an indoor environment. An error-bound is calculated between the estimated and measured robot states which is constantly adapted based on the current state and input signals. A fault is detected when the estimation error is outside this bound. The model parameters are learned by the robot using an adaptive law, after the robot deployment in the target environment. Model uncertainties have an important impact on the fault detection performance, and are dealt with by considering the uncertainty bounds in the bound calculations. This ensures no false alarms occur when the uncertainty remains bounded during normal operation. Furthermore an extension to the method is proposed that addresses the problem of detecting small faults. The method is experimentally validated on a iRobot Roomba autonomous robot.     

Motion Study of the Ornithopter with Periodic Wing Oscillations

The motion of an ornithopter, a flying robot, consisting of a body and two symmetric twolink wings, is considered. The device moves in a vertical plane perpendicular to the longitudinal axis of the robot. All the links of the object form a chain through cylindrical joints with parallel axes. A mathematical model of the ornithopter is developed based on a bird’s flight analysis taking into account the aerodynamic interaction of all the links with the environment. Sequences of flight phases are considered, each of which differs in the direction of motion of the wing links. As a result of numerical simulation, diagrams of the robot’s modes of motion are constructed (ascent, hovering, and descent) and the effect of the amplitude and frequency of oscillation of the wing links, as well as their area, is determined (the same wing area was achieved by varying the length and width of the wings).     

钢结构建筑探伤机器人刚柔耦合空间位姿解析与实验研究

针对传统钢结构建筑健康监测中存在检测盲区和检测不全面的问题,研究了磁吸附式刚柔耦合柔性探伤机器人并对其控制系统进行了改进．建立了柔性机器人前、后车体位移和姿态运动学数学模型与机器人刚柔耦合结构位姿解算方程,通过惯性测量单元和编码器获取柔性探伤机器人前、后车体实时动态位姿参数,分别采用显性互补滤波器和扩展卡尔曼滤波器解算前、后车体在不同工况中的静态、动态姿态,利用航迹推算算法确定机器人的位置,通过数据融合得到柔性机器人刚柔耦合结构的空间位姿．实验结果表明,扩展卡尔曼滤波算法的动态跟踪性能更好,可为柔性探伤机器人在复杂建筑结构越障运动中提供精确的空间位姿参数．     

Decentralized Cooperative SLAM for Sparsely-Communicating Robot Networks: A Centralized-Equivalent Approach

Communication between robots is key to performance in cooperative multi-robot systems. In practice, communication connections for information exchange between all robots are not always guaranteed, which adds difficulty in performing state estimation. This paper examines the decentralized cooperative simultaneous localization and mapping (SLAM) problem, in which each robot is required to estimate the map and all robot states under a sparsely-communicating and dynamic network. We show how the exact, centralized-equivalent estimate can be obtained by all robots in the network in a decentralized manner even when the network is never fully connected. Furthermore, a robot only needs to consider its own knowledge of the network topology in order to detect when the centralized-equivalent estimate is obtainable. Our approach is validated through more than 250 min of hardware experiments using a team of real robots. The resulting estimates are compared against accurate groundtruth data for all robot poses and landmark positions. In addition, we examined the effects of communication range limit on our algorithm’s performance.     

Dynamic computation offloading for ground and flying robots: Taxonomy,state of art,and future directions

The collaboration between ground and flying robots can take advantage of the capabilities of each system to enhance the performance of robotic applications, including military, healthcare, disaster management, etc. Unfortunately, this cooperation is restricted by the physical constraint that all computation should be performed on robots. The concept of computation offloading has great potential to improve the performance of both ground and flying robots. Unfortunately, external conditions like the network conditions, the robot’s mobility, and the availability of the processing resources may lead to new challenges. Accordingly, these challenges should be addressed from different perspectives, like security, network communication, response time, and energy consumption. Recently, most computation offloading solutions aim to optimize further the robot’s energy consumption. Several research works are designed 1.) to satisfy the real-time requirements of robotic applications and 2.) to solve the trade-off between the energy consumed by computation and communication. To better understand these concepts, we present a comprehensive overview of the computation offloading process for ground and flying robots. We also devised a taxonomy explaining the factors affecting the offloading decision in a robotic scenario. The taxonomy presents guidelines to recognize the scope of research in offloading decisions that were designed for robots. Then, we discuss the state-of-the-art techniques of computation offloading from an architectural point of view, and we survey works related to offloading decisions for robots.