给定手部作业轨迹的仿人机器人推操作研究

以推车作业为例对“汇童”仿人机器人动态行走中的推操作进行了研究,分析了手部位置与腰部位 移的关系,对作业运动中手部轨迹的补偿进行了研究．另外,作业中机器人与车之间存在相互作用,根据作业的 期望作用力,开展了基于ZMP 稳定性判据的作业运动稳定性控制研究．仿真和实验验证了该方法的有效性,它能 满足推车作业手臂操作性和运动稳定性要求．     

仿人机器人的头眼协调运动控制研究

针对机器人注视静态目标的任务,提出一种头眼协调运动的控制策略.通过使双目聚焦在同一个注视点,得到注视点的空间坐标和头眼的期望运动转角;研究了机器人头部转动时双目的补偿运动模型及相应的控制算法.实验表明,该控制策略能实现精确的3D头眼协调运动控制.     

Development of a Leg Part of a Humanoid Robot—Development of a Biped Walking Robot Adapting to the Humans' Normal Living Floor

The authors are engaged in studies of biped walking robots from thefollowing two viewpoints. One is a viewpoint as a human science. Theother is a viewpoint towards the development of humanoid robots.In this paper, the authors introduce an anthropomorphic dynamic bipedwalking robot adapting to the humans' living floor. The robot has tworemarkable systems: (1) a special foot system to obtain the positionrelative to the landing surface and the gradient of the surfaceduring its dynamic walking; (2) an adaptive walking control system toadapt to the path surfaces with unknown shapes by utilizing theinformation of the landing surface, obtained by the foot system. Twounits of the foot system WAF-3 were produced, a biped walking robotWL-12RVII that had the foot system and the adaptive walking controlsystem installed inside it was developed, and a walking experimentwith WL-12RVII was performed. As a result, dynamic biped walkingadapting to humans' floors with unknown shapes was realized. Themaximum walking speed was 1.28 s/step with a 0.3 m step length, andthe adaptable deviation range was from -16 to+16 mm/step in the vertical direction, and from-3 to +3° in the tilt angle.     

仿人形机器人火炬传递中的高精度目标特征提取

以仿人形机器人的火炬传递为背景,针对立体视觉系统的图像处理展开研究,提出了一种基于色标的高精度特征提取方法.利用火炬上的矩形色标,在RGB空间基于色彩进行图像分割,并利用K-L变换对边缘点进行分组,通过Hough变换和最小二乘法对色标边缘进行直线拟合,得到矩形色标顶点的高精度图像坐标,为提高火炬位姿测量的精度提供了基础.实验结果验证了本文方法的有效性.     

Cyber-Physical-Social System Between a Humanoid Robot and a Virtual Human Through a Shared Platform for Adaptive Agent Ecology

Two artificial agents (a humanoid robot and a virtual human) are enriched with various similar intelligence, autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physical-social system (CPSS) through a shared communication platform to create a social ecology. In the ecology, the agents collaborate (assist each other) to perform a real-world task (search for a hidden object) for the benefits of humans. A robot-virtual human bilateral trust model is derived and a real-time trust measurement method is developed. The role of taking initiative in the collaboration is switched between the agents following a finite state machine model triggered by bilateral trust, which results in a mixedinitiative collaboration. A scheme is developed to evaluate the performance of the agents in the ecology through the CPSS. The results show that the robot and the virtual human perform satisfactorily in the collaboration through the CPSS. The results thus prove the effectiveness of the real-world ecology between artificial agents of heterogeneous realities through a shared platform based on trust-triggered mixed-initiatives. The results can help develop adaptive social ecology comprising intelligent agents of heterogeneous realities to assist humans in various tasks through collaboration between the agents in the form of a CPSS.      

Whole-Body Balance Control of a Humanoid Robot in Real Time Based on ZMP Stability Regions Approach

Abstract

One of the most important and complex tasks for a humanoid robot is to avoid overturning during a bipedal gait. This work aims at setting the base for designing a general balance controller to be used with any humanoid robot. In addition, it is based on a strong simplification of humanoid model which attempts to be used in real-time applications. In particular, several “stability zones” are defined as function of the criticalness of balance. The results are presented in simulation and experimentally, using the humanoid platforms HOAP-3 and TEO.     

双臂四自由度空间机器人捕捉未知目标的参数辨识

给出了双臂四自由度空间机器人捕捉未知目标的参数辨识方法．该方法基于线动量和角动量守恒定律,推出了机械臂负载未知目标的新的末端效应器的质量、质心和转动惯量的方程组. 在线测量当机械臂运动时的本体的线速度和角速度,以求得方程组中这些未知的惯性参数．数值试验显示了该方法的有效性．     

Robot path planning in a constrained workspace by using optimal control techniques

Robot manipulators are programmable mechanical systems designed to execute a great variety of tasks in a repetitive way. In industrial environment, while productivity increases, cost reduction associated with robotic operation and maintenance can be obtained as a result of decreasing the values of dynamic quantities such as torque and jerk, with respect to a specific task. Furthermore, this procedure allows the execution of various tasks that require maximum system performance. By including obstacle avoidance ability to the robot skills, it is possible to improve the robot versatility, i.e., the robot can be used in a variety of operating conditions. In the present contribution, a study concerning the dynamic characteristics of serial robot manipulators is presented. An optimization strategy that considers the obstacle avoidance ability together with the dynamic performance associated with the movement of the robot is proposed. It results an optimal path planning strategy for a serial manipulator over time varying constraints in the robot workspace. This is achieved by using multicriteria optimization methods and optimal control techniques. Numerical simulation results illustrate the interest of the proposed methodology and the present techniques can be useful for the design of robot controllers. Commemorative contribution.     

Multi-Agent System-Based Fuzzy Controller Design with Genetic Tuning for a Mobile Manipulator Robot in the Hand Over Task

This paper presents an application of the multi-agent system approach to a service mobile manipulator robot that interacts with a human during an object delivery and hand-over task in two dimensions. The base, elbow and shoulder of the robot are identified as three different agents, and are controlled using fuzzy control. The control variables of the controllers are linear velocity of the base, angular velocity of the elbow, and angular velocity of the shoulder. Main inputs to the system are the horizontal and vertical distances between the human and robot hands. These are input to all three agents. In developing the fuzzy control rules, effective delivery and avoidance of contact with humans, not to cause physical damage, are considered. The membership functions of the fuzzy controllers are tuned by using genetic algorithms. In tuning, the performance is calculated considering the distance deviation from the direct path, time spent to reach the human hand and energy consumed by the actuators. The proposed multi-agent system structure based on fuzzy control for the object delivery task succeeded in both effective and safe delivery.