我有很多想法，大部分与机器学习以及基于目标的搜索有关。
I have lots of ideas, most have to do with Machine Learning and Goal-based Search.
代码选择在编译器的代码产生阶段是一个十分重要的任务，它的目标就是在与机器无关的中间表示代码和与处理器相关的机器指令之间寻找一种高效的映射方法。
Code selection is an important task in code generation, where the goal is to find an efficient mapping of machine-independent intermediate code to processor-specific machine instructions.
机构与机器一个系统，它按预先确定的方式来传输动力完成的具体的目标也许可以被认 为是机器。
Mechanism and Machines A system that transmits forces in a predetermined manner to accomplish specific objectives may be considered a machine.
提出了一种新的视觉定位方法，用此方法测出移动机器人与目标物体之间的相对距离。
A new method of vision location is putted forward, and can measure the relative distance between the mobile robot and goal.
提出了一种基于机器视觉与离散傅里叶变换的目标特征识别方法。利用计算机图像技术采集和处理图像信号；
A identifying image methods based on machine vision and DFT are studied, The images are collected and video signal is processed using computer technology.
设计了双回路的双轮移动机器人运动目标追踪与避障控制方案。
A moving-target tracking and obstacle avoidance control system for unicycle mobile robots is proposed in this paper.
本文采用模糊控制的方法控制移动机器人的前进方向，在模糊控制中根据障碍物的实际位置及机器人运动方向与目标点夹角的不同情况，给出了机器人的反应规则。
In fuzzy control, according to the actually obstacle position and the Angle between the target orientation and the robot's direction of movement, we give the reaction rules of the robot.
本论文的目标正是两足机器人足球肢体动作的开发与研究，工作量大、挑战性强。
The paper aimed its target at the research and exploitation of soccer body action of biped robot, which implied heavy workload and great challenge.
将社会势场与基于行为控制相结合，使得群体机器人形成聚集队形，避开未知环境中的障碍物并到达目标区域。
Social potential fields were combined with behavior-based control, which made swarm robots forming aggregation formation, avoiding the obstacles in unknown environment and reaching target area.
研究机器人与未标定关系的视觉传感系统之间的协调控制策略，其中目标运动及机器人跟踪运动均限定在二维工作平面。
This paper discusses the coordination process for a robot gripper to approach a moving object with feedback from an uncalibrated visual system.
本论文正是基于这一背景下，对架空电力线路巡检机器人目标的检测与跟踪方法做了研究。
This thesis is based on this background to do an in-depth study on target detection and tracking method for overhead power lines inspection robot.
提出了一种双目移动机器人实时动态目标识别与定位方法。
A realtime dynamic object recognition and localization method is presented for mobile robot using binocular vision.
利用手眼反馈和关节返回的信息来估计实际情况下当前机械臂末端与目标的相对位姿，进行机器人的控制。
Using the information fed back from the eye-hand controller and joints, the relative position and pose between the target and the tip of manipulator are estimated, and the controlling is made.
根据在线视觉测量结果，形成机器人的运动目标，实现焊缝自动跟踪与焊接。
The system has the function of automated recognition and tracking weld. The principle of the visual control system and LRTORC developed by us is discussed.
根据在线视觉测量结果，形成机器人的运动目标，实现焊缝自动跟踪与焊接。
The system has the function of automated recognition and tracking weld. The principle of the visual control system and LRTORC developed by us is discussed.
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