Models for the Design of Bioinspired Robot Eyes

Active vision has the goal of improving visual perception; therefore, the investigation of ocular motion strategies must play an important role in the design of humanoid robot eyes. Listing's law is a basic principle, which characterizes various ocular movements in humans, including saccades and smooth pursuit, and its neural or mechanical origin has been debated for a long time. Recent anatomical advances suggest that motions compatible with Listing's law could be mainly caused by the mechanical structure of the eye plant. In this paper, we present a bioinspired model of the eye plant, and we formally prove that according to the model, the implementation of Listing's law can be actually explained on the base of the geometry of the eye and of its actuation system. The proposed model is characterized by a limited number of geometric parameters, which can be easily used to set the guidelines for the design of humanoid, and possibly tendon-driven, robot eyes. Simulative and experimental tests performed on a robot prototype are eventually presented to perform a quantitative evaluation of the performance of the model, also in comparison with physiological data measured in humans and primates and reported in the literature.     

仿生型机器人眼球运动控制系统建模

首先，分析了人眼眼球运动的特点和形式．然后，在人眼解剖学和生理学研究的基础上，根据控制眼球运动的神经回路，建立了可实现人眼功能的仿生型机器人眼三维眼球运动控制系统的数学模型．在与生理学试验相同的条件下对该模型用Matlab 65进行了仿真实验，仿真结果与生理学实验结果对比表明，该模型能自适应地实现人眼的平滑追踪、前庭动眼反射、视动反射及其复合运动．     

Egomotion perception using visual tracking

The ability of a biological organism to visually track a perceptually significant feature in its environment has been argued to be an important feedback mechanism guiding locomotion. This paper analyzes the constraints available from the visual motion stimuli in the context of tracking. Our aim is to show that the act of tracking simplifies the decoding of egomotion parameters from motion stimuli. The constraints obtainable under tracking are utilized to analyze a possible egomotion decoding strategy for a binocular robot eye system, modeled after the human ocular tracking (smooth pursuit) mechanism. The main result of the paper is in the derivation of a closed-form solution of the egomotion parameters using feedback information concerning the movement of the tracking motors over time. The theoretical results are verified by experiments. We believe that the active tracking approach presented here is a more simple, practical, and manageable technique in a robot navigation setting, compared to passive methods.     

一种多模型融合的仿猎豹四足机器人复杂运动控制方法

针对具有 2 自由度主动脊柱关节的仿猎豹四足机器人,基于任务分解思想和生物神经系统机理,提出多模型融合的控制方法。该方法以弹簧负载倒立摆模型实现单腿跳跃控制,通过中枢模式发生器（CPG）实现 4 条腿之间以及脊柱—腿之间的协调控制,利用虚拟模型控制实现机器人与环境交互,采用基于 CPG 输出的有限状态机来融合 3 个控制模型,构建仿猎豹四足机器人的多模型分层运动控制器。参考猎豹脊柱运动特征,设计了机器人脊柱关节运动模式,给出脊柱与腿的协调控制策略。最后,在 Webots 仿真环境中搭建了仿猎豹四足机器人虚拟样机,实现了不同步态下的脊柱—腿的协调控制、在崎岖地形上稳定奔跑,以及平滑的对角—疾驰—对角步态转换,仿真结果验证了所提出的多模型融合的四足机器人运动控制方法的有效性。     

A neurocomputational model of figure-ground discrimination andtarget tracking

A neurocomputational model is presented for figure-ground discrimination and target tracking. In the model, the elementary motion detectors of the correlation type, the computational modules of saccadic and smooth pursuit eye movement, an oscillatory neural-network motion perception module and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding, and selective synchronization of phase oscillators, the figure and the ground can be successfully discriminated from each other. The receptive fields developed by hidden units of the networks were surprisingly similar to the actual receptive fields and columnar organization found in the primate visual cortex. It is suggested that equivalent mechanisms may exist in the primate visual cortex to discriminate figure-ground in both temporal and spatial domains.     

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.     

Robot, asker of questions

Collaborative control is a teleoperation system model based on human–robot dialogue. With this model, the robot asks questions to the human in order to obtain assistance with cognition and perception. This enables the human to function as a resource for the robot and help to compensate for limitations of autonomy. To understand how collaborative control influences human–robot interaction, we performed a user study based on contextual inquiry (CI). The study revealed that: (1) dialogue helps users understand problems encountered by the robot and (2) human assistance is a limited resource that must be carefully managed.     

基于DirectShow技术视频流捕捉及压缩的实现方案

提出一个基于DirectShow技术实时视频流捕捉及压缩的实现方案。该方案中视频捕捉采用WDM(视窗驱动模式)捕捉方式，提高了视频捕捉的效率和通用性；采用基于内容的MPEG-视频编码标准对视频流进行压缩．得到了较高的压缩比和压缩质量。阐述了DirectShow的技术结构及基于DirectShow视频捕捉及压缩的实现过程。     

基于时域依赖的编码树单元级零延时码率控制算法

基于高效视频编码标准的x265编码器根据图像复杂度来分配比特,复杂图像往往包含运动变化较大的高频信息,其时域相关性较弱且消耗较多比特,导致分配给运动变化平缓图像的比特减少,进而影响编码质量且码率波动较大。同时,x265编码器采用独立率失真优化技术编码,忽略了编码单元间在时域上的相关性,进而损失编码性能。针对上述问题,提出一种基于时域依赖的编码树单元级码率控制算法。首先,根据迭代策略寻找最合适的量化参数进行帧级比特分配;其次,建立零延时的失真时域反向传播模型并计算失真影响因子;最后,将失真影响因子用于调整编码单元的拉格朗日乘子及量化参数。实验结果显示,相较于x265-3.6的码率控制算法,平均BD-rate码率节省达到5.6%。     

Improving Clinician's Coded Data Entry through the Use of an Electronic Patient Record System: 3.5 Years Experience with a Semiautomatic Browsing and Encoding Tool in Clinical Routine

This report presents data on clinicians' use of a browsing and encoding utility. Traditional and computerized discharge summaries during three phases of coding ICD-9 diagnoses were compared: phase I (no coding), phase II (manual coding), and phase III (computerized semiautomatic coding). Our data indicate that only 50% of all diagnoses in a discharge summary are encoded manually; using a computerized browsing and encoding utility this rate may increase by 64%; when forced to encode diagnoses manually users may “shift” as much as 84% of relevant diagnoses from the appropriate section to other sections, thereby “bypassing” the need to encode. This effect can be partially reversed by up to 41% with the computerized approach. Using a computerized encoding help can ensure completeness of encoding data (from 46 to 100%). We conclude that the use of a computerized browsing and encoding tool by clinicians can increase data quality and the volume of documented data. Mechanisms bypassing the need to code can be reversed.     

遗传算法的编码理论与应用

编码是遗传算法求解问题的前提,文章分析了二进制编码、格雷码编码、实数编码、符号编码、排列编码、二倍体编码、DNA编码、混合编码、二维染色体编码或矩阵编码等编码的实质内容,在树编码和可变长编码基础上阐述了自适应编码的基本理论,提出了基于相似度的可变长编码和基于结构的agent编码方式,给出了函数优化、TSP、KP、JSP、机器人路径规划、图的划分和倒立摆等典型优化问题的编码方案。     

一种快速的分数位平面编码方法及其电路结构

JPEG2000是新一代图像压缩国际标准．它在位平面编码技术的基础上,进一步采用了分数位平面编码技术．分数位平面编码使编码输出的码流具有更高的渐进性和抗干扰性,但是,它使编码的运算量大幅度增加．为实现快速编码,该文提出一种位平面、过程双重并行编码方法,可以大幅度提高编码速度．另外,为降低大数量并行编码消耗的电路资源量,文中提出一种局部模块并行电路结构．实验结果显示,该文方法的编码速度约为每时钟编码一个系数,比已有技术提高约15倍．在FPGA电路平台上,只需要约4．2K的逻辑单元,因此它是一种可以通过低成本集成电路实现的快速分数位平面编码技术．     

Active Visual Perception for Mobile Robot Localization

Localization is a key issue for a mobile robot, in particular in environments where a globally accurate positioning system, such as GPS, is not available. In these environments, accurate and efficient robot localization is not a trivial task, as an increase in accuracy usually leads to an impoverishment in efficiency and viceversa. Active perception appears as an appealing way to improve the localization process by increasing the richness of the information acquired from the environment. In this paper, we present an active perception strategy for a mobile robot provided with a visual sensor mounted on a pan-tilt mechanism. The visual sensor has a limited field of view, so the goal of the active perception strategy is to use the pan-tilt unit to direct the sensor to informative parts of the environment. To achieve this goal, we use a topological map of the environment and a Bayesian non-parametric estimation of robot position based on a particle filter. We slightly modify the regular implementation of this filter by including an additional step that selects the best perceptual action using Monte Carlo estimations. We understand the best perceptual action as the one that produces the greatest reduction in uncertainty about the robot position. We also consider in our optimization function a cost term that favors efficient perceptual actions. Previous works have proposed active perception strategies for robot localization, but mainly in the context of range sensors, grid representations of the environment, and parametric techniques, such as the extended Kalman filter. Accordingly, the main contributions of this work are: i) Development of a sound strategy for active selection of perceptual actions in the context of a visual sensor and a topological map; ii) Real time operation using a modified version of the particle filter and Monte Carlo based estimations; iii) Implementation and testing of these ideas using simulations and a real case scenario. Our results indicate that, in terms of accuracy of robot localization, the proposed approach decreases mean average error and standard deviation with respect to a passive perception scheme. Furthermore, in terms of efficiency, the active scheme is able to operate in real time without adding a relevant overhead to the regular robot operation.     

Artificial potential functions based camera movements and visual behaviors in attentive robots

An attentive robot needs to exhibit a plethora of different visual behaviors including free viewing, detecting visual onsets, search, remaining fixated and tracking depending on the vision task at hand. The robot’s associated camera movements—ranging from saccades to smooth pursuit—direct its optical axis in a manner that is dependent on the current visual behavior. This paper proposes a closed-loop dynamical systems approach to the generation of camera movements based on a family of artificial potential functions. Each movement from the current fixation point to the next is associated with an artificial potential function that encodes saliency and possibly inhibition depending on the visual behavior that the robot is engaged in. The novelty of this approach is that since the nature of resulting motion can vary from being saccadic to smooth pursuit, the full repertoire of visual behaviors all become possible within the same framework. The robot can switch its visual behavior simply by changing the parameters of the constructed artificial potential functions appropriately. Furthermore, automated reflexive changes among the different visual behaviors can be achieved via a simple switching automaton. Experimental results with APES robot serve to show the performance properties of a robot engaged in each different visual behavior.     

Online-learning and Attention-based Approach to Obstacle Avoidance Using a Range Finder

The problem of developing local reactive obstacle-avoidance behaviors by a mobile robot through online real-time learning is considered. The robot operated in an unknown bounded 2-D environment populated by static or moving obstacles (with slow speeds) of arbitrary shape. The sensory perception was based on a laser range finder. A learning-based approach to the problem is presented. To greatly reduce the number of training samples needed, an attentional mechanism was used. An efficient, real-time implementation of the approach was tested, demonstrating smooth obstacle-avoidance behaviors in a corridor with a crowd of moving students as well as static obstacles.     

SnakeSIM: a ROS-based control and simulation framework for perception-driven obstacle-aided locomotion of snake robots

Biological snakes are capable of exploiting roughness in the terrain for locomotion. This feature allows them to adapt to different types of environments. Snake robots that can mimic this behaviour could be fitted with sensors and used for transporting tools to hazardous or confined areas that other robots and humans are unable to access. Snake robot locomotion in a cluttered environment where the snake robot utilises a sensory–perceptual system to perceive the surrounding operational environment for means of propulsion can be defined as perception-driven obstacle-aided locomotion (POAL). The initial testing of new control methods for POAL in a physical environment using a real snake robot imposes challenging requirements on both the robot and the test environment in terms of robustness and predictability. This paper introduces SnakeSIM, a virtual rapid-prototyping framework that allows researchers for the design and simulation of POAL more safely, rapidly and efficiently. SnakeSIM is based on the robot operating system (ROS) and it allows for simulating the snake robot model in a virtual environment cluttered with obstacles. The simulated robot can be equipped with different sensors. Tactile perception can be achieved using contact sensors to retrieve forces, torques, contact positions and contact normals. A depth camera can be attached to the snake robot head for visual perception purposes. Furthermore, SnakeSIM allows for exploiting the large variety of robotics sensors that are supported by ROS. The framework can be transparently integrated with a real robot. To demonstrate the potential of SnakeSIM, a possible control approach for POAL is considered as a case study.     

Gaze behaviour, believability, likability and the iCat

The iCat is a user-interface robot with the ability to express a range of emotions through its facial features. This article summarizes our research to see whether we can increase the believability and likability of the iCat for its human partners through the application of gaze behaviour. Gaze behaviour serves several functions during social interaction such as mediating conversation flow, communicating emotional information and avoiding distraction by restricting visual input. There are several types of eye and head movements that are necessary for realizing these functions. We designed and evaluated a gaze behaviour system for the iCat robot that implements realistic models of the major types of eye and head movements found in living beings: vergence, vestibulo ocular reflexive, smooth pursuit movements and gaze shifts. We discuss how these models are integrated into the software environment of the iCat and can be used to create complex interaction scenarios. We report about some user tests and draw conclusions for future evaluation scenarios.     

An online reference governor for mobile robot to reduce the occurrence of control input saturation

This study proposed an online reference governor for a mobile robot to reduce the occurrence of control input saturation. For following the trajectory by a mobile robot, it is one of the practical subjects to provide appropriate control reference even if any disturbances occur. We proposed a methodology to regulate the control reference iteratively based on time-scaling approach. The time-scaling approach is a method to realize to regulate time development characteristic on the given trajectory. It is difficult to model the effect of the interaction with the road surface and the trajectory tracking error is appeared as the amount of accumulated such factors. Therefore, it is a practical approach to reduce the occurrence of control input saturation based on the evaluation of the trajectory tracking error. Proposed reference governor realizes online time scaling based on the trajectory tracking error index and a smooth transition dynamics. By introducing the proposed method, the occurrence of control input saturation can be reduced in case of that the disturbances occur. For verification of our proposed method, computer simulations utilizing a stable velocity controller were conducted and the results were discussed.     

An application of Lyapunov stability analysis to improve the performance of NARMAX models

Previously we presented a novel approach to program a robot controller based on system identification and robot training techniques. The proposed method works in two stages: first, the programmer demonstrates the desired behaviour to the robot by driving it manually in the target environment. During this run, the sensory perception and the desired velocity commands of the robot are logged. Having thus obtained training data we model the relationship between sensory readings and the motor commands of the robot using ARMAX/NARMAX models and system identification techniques. These produce linear or non-linear polynomials which can be formally analysed, as well as used in place of “traditional robot” control code.In this paper we focus our attention on how the mathematical analysis of NARMAX models can be used to understand the robot’s control actions, to formulate hypotheses and to improve the robot’s behaviour. One main objective behind this approach is to avoid trial-and-error refinement of robot code. Instead, we seek to obtain a reliable design process, where program design decisions are based on the mathematical analysis of the model describing how the robot interacts with its environment to achieve the desired behaviour. We demonstrate this procedure through the analysis of a particular task in mobile robotics: door traversal.