6自由度puma機(jī)器人仿真程序源碼。This is PUMA3d.M, a 3D Matlab Kinematic model of a Puma ROBOT located in the ROBOTics lab of Walla Walla University. The file uses CAD data converted to Matlab using cad2matdemo.m, which is located on the Mathworks central file exchange. ％ ％ This file is still being developed, for the latest version check the ％ Mathworks central file exchange.
標(biāo)簽： ROBOT Kinematic located Matlab
上傳時(shí)間： 2013-12-23
上傳用戶：清風(fēng)冷雨
ROBOT open source code
標(biāo)簽： source ROBOT open code
上傳時(shí)間： 2013-12-28
上傳用戶：PresidentHuang
Wheel ROBOT Control Design，輪式移動(dòng)機(jī)器人控制電路設(shè)計(jì)，希望對(duì)你有所幫助
標(biāo)簽： Control Design Wheel ROBOT
上傳時(shí)間： 2016-08-06
上傳用戶：hwl453472107
In this paper we describe a control methodology for catching a fast moving object with a ROBOT manipulator, where visual information is employed to track the trajectory of the target. Sensing, planning and control are performed in real-time to cope with possible unpredictable trajectory changes of the moving target, and prediction techniques are adopted to compensate the time delays introduced by visual processing and by the ROBOT controller. A simple but reliable model of the ROBOT controller has been taken into account in the control architecture for improving the performance of the system. Experimental results have shown that the ROBOT system is capable of tracking and catching an object moving on a plane at velocities of up to 700 mm/s and accelerations of up to 1500 mm/s2.
標(biāo)簽： methodology describe catching control
上傳時(shí)間： 2014-01-12
上傳用戶：qq521
ALTECH ROBOT 設(shè)計(jì)電路的第一部分，提前分享設(shè)計(jì)成果
上傳時(shí)間： 2016-09-30
上傳用戶：小草123
This paper presents a visual based localization mechanism for a legged ROBOT. Our proposal, fundamented on a probabilistic approach, uses a precompiled topological map where natural landmarks like doors or ceiling lights are recognized by the ROBOT using its on-board camera. Experiments have been conducted using the AIBO Sony ROBOTic dog showing that it is able to deal with noisy sensors like vision and to approximate world models representing indoor ofce environments. The two major contributions of this work are the use of this technique in legged ROBOTs, and the use of an active camera as the main sensor
標(biāo)簽： localization mechanism presents proposal
上傳時(shí)間： 2016-11-04
上傳用戶：dianxin61
-- Simple ROBOT Control Program -------------------------------------------------------------------------- -- Left is left IR sensor - 1=object to left -- Right is rigth IR sensor - 1=object to right -- Lmotor_dir 1=forward 0=reverse -- Rmotor_dir 1=forward 0=reverse -- Lmotor_speed 111=fast 000=slow -- Rmotor_speed 111=fast 000=slow
標(biāo)簽： Control Program Simple ROBOT
上傳時(shí)間： 2013-11-27
上傳用戶：風(fēng)之驕子
-- Simple ROBOT Control Program -------------------------------------------------------------------------- library IEEE use IEEE.STD_LOGIC_1164.all use IEEE.STD_LOGIC_ARITH.all use IEEE.STD_LOGIC_UNSIGNED.all
標(biāo)簽： Control Program Simple ROBOT
上傳時(shí)間： 2014-12-22
上傳用戶：wcl168881111111
This approach addresses two difficulties simultaneously: 1) the range limitation of mobile ROBOT sensors and 2) the difficulty of detecting buildings in monocular aerial images. With the suggested method building outlines can be detected faster than the mobile ROBOT can explore the area by itself, giving the ROBOT an ability to “see” around corners. At the same time, the approach can compensate for the absence of elevation data in segmentation of aerial images. Our experiments demonstrate that ground-level semantic information (wall estimates) allows to focus the segmentation of the aerial image to find buildings and produce a ground-level semantic map that covers a larger area than can be built using the onboard sensors.
標(biāo)簽： simultaneously difficulties limitation addresses
上傳時(shí)間： 2014-06-11
上傳用戶：waitingfy
Extended Kalman Filter for ROBOT localization, mapping, SLAM. Matlab 仿真機(jī)器人應(yīng)用擴(kuò)展卡爾曼濾波器localization, mapping, SLAM.
標(biāo)簽： localization Extended mapping Kalman
上傳時(shí)間： 2013-12-27
上傳用戶：gtzj
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