Biomimetic pupils for augmenting eye emulation in humanoid robots

Contemporary approaches in the development of humanoid robots continually neglect holistic nuances, particularly in ocular prosthetic design. The standard solid glass and acrylic eye construction techniques implemented in humanoid robot design present the observer with an inaccurate representation of the natural human eye by utilising hardened synthetic materials which prohibit pupillary dynamics. Precise eye emulation is an essential factor in the development of a greater realistic humanoid robot as misrepresentation in ocular form and function will appear distinctly prevalent during proximity face to face communication as eye contact is the primary form of interpersonal communicative processing. This paper explores a new material approach in the development of a more accurate humanoid robotic eye construction by employing natural compounds similar in structure to that found in the organic human eye to replace the traditional glass and acrylic modelling techniques. Furthermore, this paper identifies a gap in current ocular system design as no robotic eye model can accurately replicate all the natural operations of the human iris simultaneously in reaction to light and emotive responsivity. This paper offers a new system design approach to augment future humanoid robot eye construction towards achieving a greater accurate and naturalistic eye emulation.     

Robot Head Motion Control with an Emphasis on Realism of Neck–Eye Coordination during Object Tracking

Important aspects of present-day humanoid robot research is to make such robots look realistic and human-like, both in appearance, as well as in motion and mannerism. In this paper, we focus our study on advanced control leading to realistic motion coordination for a humanoid’s robot neck and eyes while tracking an object. The motivating application for such controls is conversational robotics, in which a robot head “actor” should be able to detect and make eye contact with a human subject. Therefore, in such a scenario, the 3D position and orientation of an object of interest in space should be tracked by the redundant head–eye mechanism partly through its neck, and partly through its eyes. In this paper, we propose an optimization approach, combined with a real-time visual feedback to generate the realistic robot motion and robustify it. We also offer experimental results showing that the neck–eye motion obtained from the proposed algorithm is realistic comparing to the head–eye motion of humans.     

New evaluation framework for human-assistive devices based on humanoid robotics

This paper presents the new application of a humanoid robot as an evaluator of human-assistive devices. The reliable and objective evaluation framework for assistive devices is necessary for making industrial standards in order that those devices are used in various applications. In this framework, we utilize a recent humanoid robot with its high similarity to humans, human motion retargeting techniques to a humanoid robot, and identification techniques of robot’s mechanical properties. We also show two approaches to estimate supporting torques from the sensor data, which can be used properly according to the situations. With the general formulation of the wire-driven multi-body system, the supporting torque of passive assistive devices is also formulated. We evaluate a passive assistive wear ‘Smart Suit Lite (SSL)’ as an example of device, and use HRP-4 as the humanoid platform.     

仿人形机器人两眼协调运动控制系统的实现

人的两个眼球通常都是协调运动的,两个眼球各自独立地运动是不可能的。为此,我们以人的视觉生理学和解剖学研究成果为基础,对上述人的视觉机理进行研究,目的是简化人类复杂的视觉反馈系统,研制出相应的仿人形机器人视觉系统。本文主要介绍作者开发的一个仿人形机器人两眼协调运动控制系统及其控制软件。该控制系统及其控制软件可以用于实时地追踪、定位和识别活动人脸等运动目标。     

Constructive understanding and reproduction of functions of gluteus medius by using a musculoskeletal walking robot

Several factors affect the performance of humanoid walking. One factor is the complex nature of lower limbs, especially the muscles around the pelvis that contribute significantly to the stability and adaptivity of humanoid locomotion. The significance of this muscle group assures a impact on the facility of walking robots once the nature of its contribution is understood, and it can be replicated on robots. To propose a mechanical structure that facilitates walking in robots, we realized a muscle by modeling its pelvis region like that of a humanoid and developing a musculoskeletal humanoid robot. Especially, we focused on the gluteus medius, which is important for the general stability against frontal movements of the hip. Furthermore, it passively changes its influence on such motions; this is helpful during the different phases of locomotion. These changes depend on the alignment of the pelvis and femur. We confirmed the viability of the robotic gluteus medius, which was simplified to a model of two partial muscles by accomplishing the walking using this robot. This accomplishment verifies our hypothesis that using this model, the supporting functionality for the locomotion of the muscle can be reproduced and enhances the biological plausibility.     

Cyclorotation Models for Eyes and Cameras

The human visual system obeys Listing's law, which means that the cyclorotation of the eye (around the line of sight) can be predicted from the direction of the fixation point. It is shown here that Listing's law can conveniently be formulated in terms of rotation matrices. The function that defines the observed cyclorotation is derived in this representation. Two polynomial approximations of the function are developed, and the accuracy of each model is evaluated by numerical integration over a range of gaze directions. The error of the simplest approximation for typical eye movements is less than half a degree. It is shown that, given a set of calibrated images, the effect of Listing's law can be simulated in a way that is physically consistent with the original camera. This condition is important for robotic models of human vision, which typically do not reproduce the mechanics of the oculomotor system.      

Geometry and Control of Human Eye Movements

In this paper, we study the human oculomotor system as a simple mechanical control system. It is a well known physiological fact that all eye movements obey Listing's law, which states that eye orientations form a subset consisting of rotation matrices for which the axes are orthogonal to the normal gaze direction. First, we discuss the geometry of this restricted configuration space (referred to as the Listing space). Then we formulate the system as a simple mechanical control system with a holonomic constraint. We propose a realistic model with musculotendon complexes and address the question of controlling the gaze. As an example, an optimal energy control problem is formulated and numerically solved     

不同个性的情感机器人表情研究

在情感机器人研究中,不同个性的面部表情是情感机器人增强真实感的重要基础。为实现情感机器人更加丰富细腻的表情,将人类的个性特征引入情感机器人,分析个性理论和情感模型理论,得知不同个性机器人的情感强度。结合面部动作编码系统中面部表情与机器人控制点之间的映射关系,得到情感机器人不同个性的基本表情实现方法。利用Solidworks建立情感机器人脸部模型,在ANSYS工程软件中将SHFR-Ⅲ情感机器人脸部模型设置为弹性体,通过有限元仿真计算方法,对表情的有限元仿真方法进行了探究,得到实现SHFR-Ⅲ不同个性基本表情的控制区域载荷大小和仿真结果。最后,根据仿真结果,进行SHFR-Ⅲ情感机器人不同个性的表情动作实验。实验结果表明,有限元表情仿真可以指导SHFR-Ⅲ情感机器人实现近似人类的不同个性的基本面部表情。     

Autonomous online generation of a motor representation of the workspace for intelligent whole-body reaching

We describe a learning strategy that allows a humanoid robot to autonomously build a representation of its workspace: we call this representation Reachable Space Map. Interestingly, the robot can use this map to: (i) estimate the Reachability of a visually detected object (i.e. judge whether the object can be reached for, and how well, according to some performance metric) and (ii) modify its body posture or its position with respect to the object to achieve better reaching. The robot learns this map incrementally during the execution of goal-directed reaching movements; reaching control employs kinematic models that are updated online as well. Our solution is innovative with respect to previous works in three aspects: the robot workspace is described using a gaze-centered motor representation, the map is built incrementally during the execution of goal-directed actions, learning is autonomous and online. We implement our strategy on the 48-DOFs humanoid robot Kobian and we show how the Reachable Space Map can support intelligent reaching behavior with the whole-body (i.e. head, eyes, arm, waist, legs).     

一种仿人机器人跑步状态分析模型

依据仿人机器人跑步的动力学特性,通过对仿人机器人虚拟加速度传感器输出的信号进行分析,建立了仿人机器人跑步相关特征值的概率模型.针对仿人机器人的结构,分析了在整个跑步过程中惯性力和弯矩的作用,对跑步状态的影响,获取虚拟加速度传感器输出的信号,采用小波变换分析动态信号,同时进行快速傅里叶变换,在频域上提取能量特征值.使用马氏距离作为稳定跑步的判定标准,并给出了定量描述,在ADAMS软件中搭建仿人机器人,虚拟加速度传感器设置在质心处,进行跑步仿真实验,仿真实验结果表明,该模型能够反映仿人机器人的跑步特性,仿人机器人能够在跑步状态发生改变时,根据跑步特征及时调整步态,保证其稳定性.     

A Study on Acquiring Underlying Behavioral Criteria for Manipulator Motion by Focusing on Learning Efficiency

Conventional humanoid robotic behaviors are directly programmed depending on the programmer's personal experience. With this method, the behaviors usually appear unnatural. It is believed that a humanoid robot can acquire new adaptive behaviors from a human, if the robot has the criteria underlying such behaviors. The aim of this paper is to establish a method of acquiring human behavioral criteria. The advantage of acquiring behavioral criteria is that the humanoid robots can then autonomously produce behaviors for similar tasks with the same behavioral criteria but without transforming data obtained from morphologically different humans every time for every task. In this paper, a manipulator robot learns a model behavior, and another robot is created to perform the model behavior instead of being performed by a person. The model robot is presented some behavioral criteria, but the learning manipulator robot does not know them and tries to infer them. In addition, because of the difference between human and robot bodies, the body sizes of the learning robot and the model robot are also made different. The method of obtaining behavioral criteria is realized by comparing the efficiencies with which the learning robot learns the model behaviors. Results from the simulation have demonstrated that the proposed method is effective for obtaining behavioral criteria. The proposed method, the details regarding the simulation, and the results are presented in this paper.     

A Neural Model of Coordinated Head and Eye Movement Control

Gaze shifts require the coordinated movement of both the eyes and the head in both animals and humanoid robots. To achieve this the brain and the robot control system needs to be able to perform complex non-linear sensory-motor transformations between many degrees of freedom and resolve the redundancy in such a system. In this article we propose a hierarchical neural network model for performing 3-D coordinated gaze shifts. The network is based on the PC/BC-DIM (Predictive Coding/Biased Competition with Divisive Input Modulation) basis function model. The proposed model consists of independent eyes and head controlled circuits with mutual interactions for the appropriate adjustment of coordination behaviour. Based on the initial eyes and head positions the network resolves redundancies involved in 3-D gaze shifts and produces accurate gaze control without any kinematic analysis or imposing any constraints. Furthermore the behaviour of the proposed model is consistent with coordinated eye and head movements observed in primates.     

Further explorations in evolutionary humanoid robotics

The field of evolutionary humanoid robotics is a branch of evolutionary robotics specifically dealing with the application of evolutionary principles to humanoid robot design. Previous studies demonstrated the possible future potential of this approach by evolving walking behaviors for simulated humanoid robots with up to 20 degrees of freedom. In this paper we examine further the evolutionary process by looking at the changes in diversity over time. We then investigate the effect of the immobilization of an individual joint or joints in the robot. The latter study may be of potential future use in prosthetic design. We also explore the possibility of the evolution of humanoid robots which can cope with different environmental conditions. These include reduced ground friction (ice) and modified gravitation (moon walking). We present initial results on the implementation of our simulated humanoid robots in hardware using the Bioloid robotic platform, using a model of this robot in order to evolve the desired motion patterns, for subsequent transfer to the real robot. We finish the article with a summary and brief discussion of future work. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

HRP-2W: A humanoid platform for research on support behavior in daily life environments

We introduce a concept of a real-world-oriented humanoid robot that can support humans’ activities in daily life. In such environments, robots have to watch humans, understand their behavior, and support their daily life tasks. In particular, these robots must be capable of such real-world behavior as handling tableware and delivering daily commodities by hand. We developed a humanoid robot, HRP-2W, which has an upper body of HRP-2 [K. Kaneko, F. Kanehiro, S. Kajita, H. Hirukawa, T. Kawasaki, M. Hirata, K. Akachi, T. Isozumi, Humanoid Robot HRP-2, in: Proceedings of the 2004 IEEE International Conference on Robotics & Automation, 2004, pp. 1083–1090] and a wheel module instead of legs, as a research platform to fulfill this aim. We also developed basic software configuration in order to integrate our platform with other research groups. Through experiments, we demonstrated the feasibility of the humanoid robot platform and the potential of the software architecture.     

Robotic eyes that express personality

ABSTRACT

We create robots to help people, and we believe that our robots can be more helpful if they look and behave as humans do. People usually prefer help from those whom they like. Some people can be likeable for their personality. A robot, especially an android, may become likeable too if it expresses likeable personality. A robot, or at least an android, needs the ability to express personality such that it can become more likeable, that its help can be more readily accepted. As the first step, we have investigated how the robotic eyes of an android may express personality. Humans have expressive eyes. We postulate that human eyes express personality. We experimented to see whether our test subjects could perceive distinct personalities in an android we programmed to imitate the eye movements of two people. The result showed that the android did express distinct personalities, but not without limitations.     

Redundancy Control of a Humanoid Head for Foveation and Three-Dimensional Object Tracking: A Virtual Mechanism Approach

This paper presents a novel approach for object tracking with a humanoid robot head. The proposed approach is based on the concept of a virtual mechanism, where the real head is enhanced with a virtual link that connects the eye with a point in three-dimensional space. We tested our implementation on a humanoid head with 7 d.o.f. and two rigidly connected cameras in each eye (wide-angle and telescopic). The experimental results show that the proposed control algorithm can be used to maintain the view of an observed object in the foveal (telescopic) image using information from the peripheral view. Unlike other methods proposed in the literature, our approach indicates how to exploit the redundancy of the robot head. The proposed technique is systematic and can be easily implemented on different types of active humanoid heads. The results show good tracking performance regardless of the distance between the object and the head. Moreover, the uncertainties in the kinematic model of the head do not affect the performance of the system.     

Designing a sociable humanoid robot for interdisciplinary research

This paper presents the humanoid robot BARTHOC and the smaller, but system-equal twin, BARTHOC Junior. Both robots have been developed to study human–robot interaction. The main focus of BARTHOC's design was to realize the expression and behavior of the robot to be as human-like as possible. This allows us to apply the platform to manifold research and demonstration areas. With its human-like look and mimic possibilities it differs from other platforms like ASIMO or QRIO and enables experiments even close to Mori's 'uncanny valley'. The paper describes details of the mechanical and electrical design of BARTHOC together with its PC control interface and an overview of the interaction architecture. Its humanoid appearance allows limited imitation of human behavior. The basic interaction software running on BARTHOC has been completely ported from a mobile robot except for some functionalities that could not be used due to hardware differences such as the lack of mobility. Based on these components, the robot's human-like appearance will enable us to study embodied interaction and to explore theories of human intelligence.     

Biologically inspired design of a parallel actuated humanoid robot

This paper presents the comparison for the role of bi-articular and mono-articular actuators in human and bipedal robot legs, in particular the hip and knee joint, for driving the design of a humanoid robot with inspirations from the biological system. The various constraints driving the design of both systems are also compared. Additional factors particular to robotic system are identified and incorporated in the design process. To do this, a dynamic simulation is used to determine loading conditions and the forces and power produced by each actuator under various arrangements. It is shown that while the design principles of humans and humanoids are similar, other constraints ensure that robots are still merely inspired by humans, and not direct copies. A simple design methodology that captures the complexity and constraints of such a system in this paper is proposed. Finally, a full-size humanoid robot that demonstrates the newfound principle is highlighted.     

A machine learning based intelligent vision system for autonomous object detection and recognition

Existing object recognition techniques often rely on human labeled data conducting to severe limitations to design a fully autonomous machine vision system. In this work, we present an intelligent machine vision system able to learn autonomously individual objects present in real environment. This system relies on salient object detection. In its design, we were inspired by early processing stages of human visual system. In this context we suggest a novel fast algorithm for visually salient object detection, robust to real-world illumination conditions. Then we use it to extract salient objects which can be efficiently used for training the machine learning-based object detection and recognition unit of the proposed system. We provide results of our salient object detection algorithm on MSRA Salient Object Database benchmark comparing its quality with other state-of-the-art approaches. The proposed system has been implemented on a humanoid robot, increasing its autonomy in learning and interaction with humans. We report and discuss the obtained results, validating the proposed concepts.     

仿人机器人的机械结构设计与控制系统构建

文章研发了一款适用于机器人教育教学的多功能、多用途、普适性的19自由度的小型仿人机器人,主要完成了该机器人的机械结构设计与控制系统构建工作[1]。所设计的机器人机械结构可靠性高、工艺性好、结构紧凑、样式新颖；所构建的机器人控制系统鲁棒性高、稳定性好、控制准确、反应迅速,圆满地实现了预期的设计任务。通过对优缺点的综合对比,得出组合式构型方案在功能性、实用性和稳定性等方面具有明显优势,有望通过后续软件系统的开发提高其运动效能,真正在青少年机器人教育中发挥重要作用[2]。