Planetary exploration by robotic aerovehicles

Planetary aerobots are a new type of telerobotic science platform that can fly and navigate in a dynamic 3-dimensional atmospheric environment, thus enabling the global in situ exploration of planetary atmospheres and surfaces. Aerobots are enabled by a new concept in planetary balloon altitude control, developed at JPL, which employs reversible-fluid changes to permit repeated excursions in altitude. The essential physics and thermodynamics ofreversible-fluid altitude control have been demonstrated in a series of altitude-control experiments conducted in the Earth's atmosphere, which are described. Aerobot altitude-control technology will be important in the exploration of seven planets and satellites in our solar system. Three of these objects—Venus, Mars, and the Saturnian satellite Titan—have accessible solid surfaces and atmospheres dominated by the dense gases nitrogen or carbon dioxide. They will be explored with aerobots using helium or hydrogen as their primary means of buoyancy. The other four planets—Jupiter, Saturn, Uranus, and Neptune—have deep atmospheres that are predominantly hydrogen. It may be possible to explore these atmospheres with aerobots inflated with atmospheric gas that is then radiatively heated from the hotter gaseous depths below. To fulfill their potential, aerobots to explore the planets will need autonomous state estimators to guide their observations and provide information to the altitude-control systems. The techniques of acquiring these data remotely are outlined. Aerobots will also use on board altitude control and navigation systems to execute complex flight paths including descent to the surface and exploiting differential wind velocities to access different latitude belts. Approaches to control of these systems are examined. The application of aerobots to Venus exploration is explored in some detail: The most ambitious mission described, the Venus Flyer Robot (VFR), would have the capability to make repeated short excursions to the high-temperature surface environment of Venus to acquire data and then return to the Earth-like upper atmosphere to communicate and recool its electronic systems. Finally a Planetary Aerobot Testbed is discussed which will conduct Earth atmospheric flights to validate autonomous-state-estimator techniques and flight-path-control techniques needed for future planetary missions.     

A real-time planning algorithm for obstacle avoidance of redundant robots

A computationally efficient, obstacle avoidance algorithm for redundant robots is presented in this paper. This algorithm incorporates the neural networks and pseudodistance function D _p in the framework of resolved motion rate control. Thus, it is well suited for real-time implementation. Robot arm kinematic control is carried out by the Hopfield network. The connection weights of the network can be determined from the current value of Jacobian matrix at each sampling time, and joint velocity commands can be generated from the outputs of the network. The obstacle avoidance task is achieved by formulating the performance criterion as D _p>d _min (d _min represents the minimal distance between the redundant robot and obstacles). Its calculation is only related to some vertices which are used to model the robot and obstacles, and the computational times are nearly linear in the total number of vertices. Several simulation cases for a four-link planar manipulator are given to prove that the proposed collision-free trajectory planning scheme is efficient and practical.     

人体步行规律与仿人机器人步态规划

从仿生学角度分析了人体的步行运动规律,提出了一种基于人体运动规律的仿人机器人步态参数设定方法.首先对人体步行运动数据进行捕捉并分析,得出人体各步态参数间的函数关系,以人体步行相似性作为评价指标,提出仿人机器人步态参数的设定方法.其次,通过分析人体在步行过程中的补偿支撑脚偏航力矩的基本原理,提出了基于双臂及腰关节协调运动的仿人机器人偏航力矩补偿算法,以提高仿人机器人行走的稳定性.最后通过仿真及实验验证了所提出的步态规划方法的正确性及有效性.     

一种基于光照变化补偿的颜色识别方法

针对RoboCup中型组足球机器人比赛中光照变化会使颜色发生色彩漂移,影响颜色识别的准确性问题,提出一种基于光照变化补偿的颜色识别方法。该方法首先利用球的历史信息预测球的位置,然后在较小的区域内用基于色调直方图反向投影的方法找到球后,通过球的亮度直方图的变化计算出光照变化率,用于动态补偿颜色查找表。实验表明该方法能提高颜色识别的光照自适应性。     

Robust pole assignment for incomplete nonlinear decoupling applied to robots

A robustness analysis and synthesis for incomplete nonlinear decoupling for a class of nonlinear systems is discussed. Rigid and elastic-joint robot models belong to this class. For the elastic case, a transformation facilitates the robustness analysis under a weak assumption. Charts with H ₁- and H - norms of closed-loop disturbance transfer functions of the nonlinear-decoupled system are presented for a robust pole assignment.     

An Intelligent Robust Tracking Control for a Class of Electrically Driven Mobile Robots

This paper addresses the problem of designing robust tracking control for a class of uncertain wheeled mobile robots actuated by brushed direct current motors. This class of electrically‐driven mechanical systems consists of the robot kinematics, the robot dynamics, and the wheel actuator dynamics. Via the backstepping technique, an intelligent robust tracking control scheme that integrates a kinematic controller and an adaptive neural network‐based (or fuzzy‐based) controller is developed such that all of the states and signals of the closed‐loop system are bounded and the tracking error can be made as small as possible. Two adaptive approximation systems are constructed to learn the behaviors of unknown mechanical and electrical dynamics. The effects of both the approximation errors and the unmodeled time‐varying perturbations in the input and virtual‐input weighting matrices are counteracted by suitably tuning the control gains. Consequently, the robust control scheme developed here can be employed to handle a broader class of electrically‐driven wheeled mobile robots in the presence of high‐degree time‐varying uncertainties. Finally, a simulation example is given to demonstrate the effectiveness of the developed control scheme.     

霍夫空间中多足球机器人协作目标定位算法

针对嵌入式仿人足球机器人提出一种霍夫空间中的多机器人协作目标定位算法。机器人利用实验场地中的标志物采用基于三角几何定位方法进行自定位,把机器人多连杆模型进行简化,通过坐标系位姿变换把图像坐标系转换到世界坐标系中,实现机器人目标定位;在多机器人之间建立ZigBee无线传感器网络进行通信,把多个机器人定位的坐标点进行霍夫变换,在霍夫空间中进行最小二乘法线性拟合,获取最优参数,然后融合改进后的粒子滤波实现对目标小球的跟踪;最后在21自由度的仿人足球机器人上进行仿真和实验。数据结果表明,这种多机器人协作的定位算法的精度提高了约48%,在满足实时性的前提下,对目标的跟踪效果也得到了改善。     

一种引入通信的多移动机器人编队方法*

提出以视觉跟踪为基础并引入通信进行多机器人的编队控制方法,根据需要编写了一种新的通信协议,采用闭环l-Φ实现编队算法.这种多机器人编队控制避免了视觉系统的局限,能够更好地在复杂未知环境中协作完成任务,解决了编队控制的无反馈和实时性不高的问题,使得机器人能够准确迅速地进行跟踪和通信编队,一起顺利达到目标点.试验结果证明了该方法的有效性.     

Cable-direct-driven-robot (CDDR) with a 3-link passive serial support

Cable-direct-driven-robots (CDDRs) provided with a passive serial support represent an interesting and rising evolution of planar cable robots. The paper is devoted to present and analyze a novel CDDR robot. The robot consists in a fully actuated CDDR supported against loading normal to the motion plane with a 3-link passive planar serial manipulator. This hybrid structure combines positive features of both parallel and serial architectures, and prevents out-of-plane movements without the necessity for the robot to be supported on the motion plane. The adoption of a 3-link serial manipulator ensures a greater workspace area compared with similar structures that adopt a smaller number of links, and improves specific characteristics of their dynamics. Nevertheless undesired oscillations may occur since the serial manipulator is underconstrained. For this reason damping elements are inserted in the structure. Simulation examples are presented to demonstrate the novel CDDR concept and its dynamics. In addition, a strategy to select proper values of damping coefficients is presented.     

An open-source multi-DOF articulated robotic educational platform for autonomous object manipulation

This research presents an autonomous robotic framework for academic, vocational and training purpose. The platform is centred on a 6 Degree Of Freedom (DOF) serial robotic arm. The kinematic and dynamic models of the robot have been derived to facilitate controller design. An on-board camera to scan the arm workspace permits autonomous applications development. The sensory system consists of position feedback from each joint of the robot and a force sensor mounted at the arm gripper. External devices can be interfaced with the platform through digital and analog I/O ports of the robot controller. To enhance the learning outcome for beginners, higher level commands have been provided. Advanced users can tailor the platform by exploiting the open-source custom-developed hardware and software architectures. The efficacy of the proposed platform has been demonstrated by implementing two experiments; autonomous sorting of objects and controller design. The proposed platform finds its potential to teach technical courses (like Robotics, Control, Electronics, Image-processing and Computer vision) and to implement and validate advanced algorithms for object manipulation and grasping, trajectory generation, path planning, etc. It can also be employed in an industrial environment to test various strategies prior to their execution on actual manipulators.