Development of a quadruped walking robot AiDIN-III using biologically inspired kinematic analysis

This paper presents a bio-inspired mechanism design for a quadruped walking robot. The approach is derived from the observation on the behaviors of quadruped locomotion, skeletal structure, and the study on the stability of walking based on morphological analysis. In the first, we define the design parameters such as the dimensions of the body and limbs, the center of mass position, and locomotion mechanisms based on surveys on the literatures from biologists. Then, by using the parameters, we propose an useful framework for determining the design parameters of a quadruped walking robot. For implementations, we manufacture a dog-type self-contained quadruped walking robot, named AiDIN-III (Artificial Digitigrade for Natural Environment version III) and the effectiveness of the proposed idea is validated via experimental works.     

Attentive behavior in an anthropomorphic robot vision system

Powerful data reduction and selection processes, such as selective attention mechanisms and space-variant sensing in humans, can provide great advantages for developing effective real-time robot vision systems. The use of such processes should be closely coupled with motor capabilities, in order to actively interact with the environment. In this paper, an anthropomorphic vision system architecture integrating retina-like sensing, hierarchical structures and selective attention mechanisms is proposed. Direction of gaze is shifted based on both the sensory and semantic characteristics of the visual input, so that a task-dependent attentive behavior is produced. The sensory features currently included in the system are related to optical flow invariants, thus providing the system with motion detection capabilities. A neural network architecture for visual recognition is also included, which produces semantic-driven gaze shifts.     

Pneumatic-driven jumping robot with anthropomorphic muscular skeleton structure

Human muscular skeleton structure plays an important role for adaptive locomotion. Understanding of its mechanism is expected to be used for realizing adaptive locomotion of a humanoid robot as well. In this paper, a jumping robot driven by pneumatic artificial muscles is designed to duplicate human leg structure and function. It has three joints and nine muscles, three of them are biarticular muscles. For controlling such a redundant robot, we take biomechanical findings into account: biarticular muscles mainly contribute to joint coordination whereas monoarticular muscles contribute to provide power. Through experiments, we find (1) the biarticular muscles realize coordinated movement of joints when knee and/or hip is extended, (2) the extension of the ankle does not lead to coordinated movement, and (3) we can superpose extension of the knee with that of the hip without losing the joint coordination. The obtained knowledge can be used not only for robots, but may also contribute to understanding of adaptive human mechanism.     

拟人机器人视觉系统的软件设计

清华大学“985”重点科研项目——拟人机器人技术和应用系统研究开发的拟人机器人TBIPR-I包括视觉系统，系统新的软件部分应用了Direct Show技术，采用了组件的形式实现了主要部分。将新旧系统进行了对比，并给出了部分代码实例。     

Growth and repair: Instantiating a biologically inspired model of neuronal development on the Khepera robot

Activity-dependent, developmental synaptic plasticity permits, in part, an animal’s nervous system to be constructed in a way that depends on both the animal’s experiences and its body’s particular morphology. The continuing expression of this plasticity into later life allows constant adaptation of the animal’s nervous system to changes in the animal’s body as it grows and ages, also allowing some recovery from major injury. We instantiate a previously studied model of such neuronal development on a robotic platform to establish whether “developmental robotics” can equip a robot with a nervous system tuned to the robot’s individual morphology and that allows recovery from damage.     

Modeling, simulation and fuzzy control of an anthropomorphic robot arm by using Dymola

Analysis and fuzzy control of an anthropomorphic robot arm on a special trajectory is the subject of this paper. These types of systems are used in cutting operations on materials, joining materials by welding, material handling in remote and dangerous environments, packing of foods, inspection/testing electronic parts or medical products. This robot arm realizes the handling motion on a special trajectory. In this study, the first three links of Mitsubishi RV-2AJ Industrial Robot, are like an anthropomorphic arm, have been modeled and simulated by using Dymola. Kinematic equations have been obtained and mathematical model of this system has been formed by using Lagrange’s Equations. Fuzzy logic controller for the joint angles for the motion trajectory has been designed and the simulation results have been presented at the end of the study.     

Biologically inspired control of quadruped walking robot

In this paper, we present a control method for a quadruped walking robot inspired from the locomotion of quadrupeds. A simple and useful framework for controlling a quadruped walking robot is presented, which is obtained by observing the stimulus-reaction mechanism, the gravity load receptor and the manner of generating repetitive motions from quadrupeds. In addition, we propose a new rhythmic pattern generator that can relieve the large computational burden on solving the kinematics. The proposed method is tested via a dynamic simulation and validated by implementation in a quadruped walking robot, called AiDIN-I (Artificial Digitigrade for Natural Environment I). Recommended by Editorial Board member Sangdeok Park under the direction of Editor Jae-Bok Song. This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD) (KRF-2005-D00031). Ig Mo Koo received the B.S. degree in Mechanical Engineering from Myongji University, Yongin, Korea, in 2003, the M.S. degree in Mechanical Engineering from the Sungkyunkwan University, Suwon, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical Engineering from Sungkyunkwan University. His research interests include artificial muscle actuators, haptics, tactile display, biomimetics and quadruped walking robots systems. Tae Hun Kang received the B.S., M.S., and Ph.D. degrees in Mechanical Engineering from Sungkyunkwan University, Korea, in 2000, 2002, and 2006, respectively. His current research interests focus on biomimetics and quadruped walking robot. Gia Loc Vo received the B.S degree in Mechanical Engineering form Ha Noi University of Technology in Vietnam 2003, the M.S. degree Mechanical Engineering form Sungkyunkwan University, Suwon, Korea, in 2006, where he is currently working toward a Ph.D. degree in Mechanical Engineering from Sungkyunkwan University. His research interests include legged locomotion, walking and climbing robot. Tran Duc Trong received the B.S degree in Mechatronics from HoChiMinh City University of Technology in Vietnam in 2005, where he is currently working toward a M.S. degree in Mechanical Engineering from Sungkyunkwan University. His research interests include biological inspired control and adaptive control of quadruped walking robot. Young Kuk Song received the B.S. degree in Mechanical Engineering from Sungkyunkwan University, Suwon, Korea, in 2006, where he is currently working toward a M.S. degree in Mechanical Engineering from Sungkyunkwan University. His research interests include biomimetics, hydraulic robotics system and quadruped walking robot. Hyouk Ryeol Choi received the B.S. degree from Seoul National University, Seoul, Korea, in 1984, the M.S. degree from the Korea Advanced Technology of Science and Technology (KAIST), Daejeon, Korea, in 1986, and the Ph.D. degree from the Pohang University of Science and Technology (POSTECH), Pohang, Korea, in 1994. Since 1995, he has been with Sungkyunkwan University, Suwon, Korea, where he is currently a Professor in the School of Mechanical Engineering. He was an Associate Engineer with LG Electronics Central Research Laboratory, Seoul, Korea, from 1986 to 1989. From 1993 to 1995, he was with Kyoto University, Kyoto, Japan, as a grantee of scholarship funds from the Japanese Educational Administry. He visited the Advanced Institute of Industrial Science Technology (AIST), Tsukuba, Japan, as a JSPS Fellow from 1999 to 2000. He is now an Associate Editor in IEEE Transactions on Robotics, Journal of Intelligent Service Robotics, International Journal of Control, Automation and Systems (IJCAS). His interests includes dexterous mechanisms, field application of robots, and artificial muscle actua tors.     

Realization of sign language motion using a dual-arm/hand humanoid robot

The recent increase in technological maturity has empowered robots to assist humans and provide daily services. Voice command usually appears as a popular human–machine interface for communication. Unfortunately, deaf people cannot exchange information from robots through vocal modalities. To interact with deaf people effectively and intuitively, it is desired that robots, especially humanoids, have manual communication skills, such as performing sign languages. Without ad hoc programming to generate a particular sign language motion, we present an imitation system to teach the humanoid robot performing sign languages by directly replicating observed demonstration. The system symbolically encodes the information of human hand–arm motion from low-cost depth sensors as a skeleton motion time-series that serves to generate initial robot movement by means of perception-to-action mapping. To tackle the body correspondence problem, the virtual impedance control approach is adopted to smoothly follow the initial movement, while preventing potential risks due to the difference in the physical properties between the human and the robot, such as joint limit and self-collision. In addition, the integration of the leg-joints stabilizer provides better balance of the whole robot. Finally, our developed humanoid robot, NINO, successfully learned by imitation from human demonstration to introduce itself using Taiwanese Sign Language.     

The value of multiple independent robot arms

When multiple independent robot arms attempt to perform concurrent operations at the same work cell, spatial interference imposes limits on the degree of parallelism that can be achieved. It is shown that as the number of independent arms approaches infinity, the degree of parallelism is bounded. Mathematical limiting values are derived for the extent of parallelism for two cases of an idealized simplistic application. The main value of these results is to demonstrate that under conditions of spatial contention, there is little merit in having more than two independent arms at a work cell. Designing the work cell to reduce contention increases the value of multiple independent arms.     

In the footsteps of Leonardo [articulated anthropomorphic robot]

Leonardo da Vinci's powerful approach of linking kinesiology and anatomy, and translating them into kinematics and structure is a model for future lines of research. This application of Leonardo's approach has lead to the development of a new kinematic architecture that is being used to meet NASA's requirements for a robotic surrogate to aid astronauts in space station construction, maintenance and expansion. Various commercial applications are envisaged for the robotic surrogate     

On tracking control of flexible robot arms

A controller for solving the tracking problem of flexible robot arms is presented. In order to achieve this goal, the desired trajectory for the link (flexible) coordinates is computed from the dynamic model of the robot arm and is guaranteed to be bounded, and the desired trajectory for the joint (rigid) coordinates can be assigned arbitrarily. The case of no internal damping is also considered, and a robust control technique is used to enhance the damping of the system     

A taxonomy of biologically inspired research in computer networking

The natural world is enormous, dynamic, incredibly diverse, and highly complex. Despite the inherent challenges of surviving in such a world, biological organisms evolve, self-organize, self-repair, navigate, and flourish. Generally, they do so with only local knowledge and without any centralized control. Our computer networks are increasingly facing similar challenges as they grow larger in size, but are yet to be able to achieve the same level of robustness and adaptability. Many research efforts have recognized these parallels, and wondered if there are some lessons to be learned from biological systems. As a result, biologically inspired research in computer networking is a quickly growing field. This article begins by exploring why biology and computer network research are such a natural match. We then present a broad overview of biologically inspired research, grouped by topic, and classified in two ways: by the biological field that inspired each topic, and by the area of networking in which the topic lies. In each case, we elucidate how biological concepts have been most successfully applied. In aggregate, we conclude that research efforts are most successful when they separate biological design from biological implementation – that is to say, when they extract the pertinent principles from the former without imposing the limitations of the latter.     

Optimal design of microfluidic networks using biologically inspired principles

From the earliest of times, Man has sought to replicate ideas that have evolved naturally in plants and animals. Understanding and extracting these “natural” design strategies has opened up a whole new field of research known as biomimetics. Designs formulated using biologically inspired principles range from novel surface treatments that mimic physiological processes to geometrical optimization for improving the performance of a system. In this paper, we will show how biomimetic principles based on the laws that govern biological vascular trees can be used to design artificial microfluidic distribution systems. The study focuses specifically on microfluidic manifolds composed of constant-depth rectangular- or trapezoidal-sectioned channels, as these geometries can readily be fabricated using standard micro-fabrication techniques. We will show that it is possible to introduce a prescribed element of flow control into the system by carefully selecting the branching parameter that governs the change in channel dimension at each bifurcation.     

On biologically inspired predictions of the global financial crisis

Early-warning models provide means for ex ante identification of elevated risks that may lead to a financial crisis. This paper taps into the early-warning literature by introducing biologically inspired models for predicting systemic financial crises. We create three models: a conventional statistical model, a back-propagation neural network (NN) and a neuro-genetic (NG) model that uses a genetic algorithm for choosing the optimal NN configuration. The models are calibrated and evaluated in terms of usefulness for policymakers that incorporates preferences between type I and type II errors. Generally, model evaluations show that biologically inspired models outperform the statistical model. NG models are, however, shown not only to provide largest usefulness for policymakers as an early-warning model, but also in form of decreased expertise and labor needed for, and uncertainty caused by, manual calibration of an NN. For better generalization of data-driven models, we also advocate adopting to the early-warning literature a training scheme that includes validation data.     

Forcefree control with independent compensation for industrial articulated robot arms

Forcefree control of robot manipulators so far has been the passive motion of the arm due to the influence of external force under ideal conditions of zero gravity and zero friction, whereas this paper demonstrates forcefree control under assigned friction, gravity and inertia. The effectiveness of the proposed forcefree control with independent compensation is confirmed by comparing the experimental results with simulation results. Comparisons of the forcefree control with independent compensation to the other force control methods are also presented.     

双摇臂履带式矿山机器人结构优化设计

针对双摇臂履带式矿山机器人结构设计中的多目标优化问题,提出了基于GA-PSO算法的双摇臂履带式矿山机器人结构优化设计方案。通过机器人越障过程的几何学和运动学分析,得出机器人越障最大高度和质心位置变换的影响因素;根据矿山机器人工作要求建立约束条件,得到多目标优化函数,通过引入权重系数,将多目标优化问题转换为单目标优化问题;利用GA-PSO算法对单目标优化问题进行求解,得到机器人最优结构参数:车体质量为10kg,摇臂质量为5kg,前后轮距离为600 mm,驱动轮半径为115mm。仿真结果表明,采用该结构参数设计的机器人完成目标动作所需的能耗低于其他设计方案,更加易于实现目标动作。     

Processing of chemical sensor arrays with a biologically inspired model of olfactory coding

This paper presents a computational model for chemical sensor arrays inspired by the first two stages in the olfactory pathway: distributed coding with olfactory receptor neurons and chemotopic convergence onto glomerular units. We propose a monotonic concentration-response model that maps conventional sensor-array inputs into a distributed activation pattern across a large population of neuroreceptors. Projection onto glomerular units in the olfactory bulb is then simulated with a self-organizing model of chemotopic convergence. The pattern recognition performance of the model is characterized using a database of odor patterns from an array of temperature modulated chemical sensors. The chemotopic code achieved by the proposed model is shown to improve the signal-to-noise ratio available at the sensor inputs while being consistent with results from neurobiology.     

A parameter identification method of horizontal robot arms

In order to develop an advanced control system and a simulation system for a robot arm, it is necessary to establish an accurate identification method for a dynamical model. The parameters of the dynamical model of a robot arm consist of the link length, the position of the centre of mass, the mass of the link, viscous damping, and Coulomb friction. However, it is not necessary to estimate these parameters independently because if several combined constants appearing in the equation of motion are obtained, then the control and simulation can be done using only these combined constants. In this paper, first we show that viscous damping and Coulomb friction are obtained by measuring the relation between the current and angular velocity. Then we propose an effective identification method of inertial terms using the mechanical resonance occurring due to the stiffness of the joints.     

Integrating a flexible anthropomorphic, robot hand into the control, system of a humanoid robot

This article presents the approaches taken to integrate a novel anthropomorphic robot hand into a humanoid robot. The requisites enabling such a robot hand to use everyday objects in an environment built for humans are presented. Starting from a design that resembles the human hand regarding size and movability of the mechatronical system, a low-level control system is shown providing reliable and stable controllers for single joint angles and torques, entire fingers and several coordinated fingers. Further on, the high-level control system connecting the low-level control system with the rest of the humanoid robot is presented. It provides grasp skills to the superior robot control system, coordinates movements of hand and arm and determines grasp patterns, depending on the object to grasp and the task to execute. Finally some preliminary results of the system, which is currently tested in simulations, will be presented.