After a coal mine disaster,especially a gas and coal dust explosion,the space-restricted and unstructured underground terrain and explosive gas require coal mine rescue robots with good obstacle-surmounting performanc...After a coal mine disaster,especially a gas and coal dust explosion,the space-restricted and unstructured underground terrain and explosive gas require coal mine rescue robots with good obstacle-surmounting performance and explosion-proof capability. For this type of environment,we designed a mobile platform for a rocker-type coal mine rescue robot with four independent drive wheels.The composition and operational principles of the mobile platform are introduced,we discuss the flameproof design of the rocker assembly,as well as the operational principles and mechanical structure of the bevel gear differential and the main parameters are provided.Motion simulation of the differential function and condition of the robot running on virtual,uneven terrain is carried out with ADAMS.The simulation results show that the differential device can maintain the main body of the robot at an average angle between two rockers.The robot model has good operating performance.Experiments on terrain adaptability and surmounting obstacle performance of the robot prototype have been carried out.The results indicate that the prototype has good terrain adaptability and strong obstacle-surmounting performance.展开更多
A new explosion-proof walking system was designed for the coal mine rescue robot(CMRR) by optimizing the mechanical structure and control algorithm. The mechanical structure innovation lies mainly in the dual-motor dr...A new explosion-proof walking system was designed for the coal mine rescue robot(CMRR) by optimizing the mechanical structure and control algorithm. The mechanical structure innovation lies mainly in the dual-motor drive tracked unit used, which showed high dynamic performance compared with the conventional tracked unit. The control algorithm, developed based on decision trees and neural networking, facilitates autonomous switching between "Velocity-driven Mode" and "Torquedriven Mode". To verify the feasibility and effectiveness of the control strategy, we built a self-designed test platform and used it to debug the control program; we then made a robot prototype and conducted further experiments on single-step, ramp, and rubble terrains. The results show that the proposed walking system has excellent dynamic performance and the control strategy is very efficient, suggesting that a robot with this type of explosion-proof walking system can be successfully applied in Chinese coal mines.展开更多
With the long-term use of coal bunker, a certain amount of sticking objects will beformed on its wall, and coal mine clearing robot can replace man in clearing the bunker wall.Also, since it equip with an explosion-pr...With the long-term use of coal bunker, a certain amount of sticking objects will beformed on its wall, and coal mine clearing robot can replace man in clearing the bunker wall.Also, since it equip with an explosion-proof camera, the worker can determine the operationby observing the well-head monitor.Moreover, it cannot work unless it is placed in positionand supported stably, and it has three degrees of freedom: rotating, stretching, and shovelcoal.It is driven by the hydraulic and controlled by PLC.The underground coal mine clearingrobot changs the traditional clearing methods, man does not have to enter the bunker toclear it, which ensures the production safety of coal transportation.展开更多
针对煤矸石分拣机器人分拣煤矸石时,带式输送机输送带打滑、跑偏以及带速波动造成的目标煤矸石位姿变化,从而导致抓取失败或空抓漏抓等问题,提出了一种改进的ORB-FLANN (Oriented FAST and Rotated BRIEF-Fast Library for Approximate ...针对煤矸石分拣机器人分拣煤矸石时,带式输送机输送带打滑、跑偏以及带速波动造成的目标煤矸石位姿变化,从而导致抓取失败或空抓漏抓等问题,提出了一种改进的ORB-FLANN (Oriented FAST and Rotated BRIEF-Fast Library for Approximate Nearest Neighbors)煤矸石识别图像与分拣图像高效匹配方法。提出改进ORB的特征点检测方法对煤矸石识别图像与分拣图像进行特征点检测,实现快速检测图像特征点;提出改进FLANN匹配算法对图像特征点进行匹配,实现煤矸石识别图像与分拣图像高效匹配。针对传统ORB方法对煤矸石图像特征检测时间长、重复率低问题,提出了改进ORB特征检测方法,提高了图像特征点检测速度和重复率;针对传统FLANN匹配方法对煤矸石图像匹配精确率低问题,提出了融合PROSAC算法的改进FLANN匹配方法,剔除错误特征匹配点对,提高了图像匹配的精确率。在自主研发的双机械臂桁架式煤矸石分拣机器人试验平台上应用文中方法、SURF特征匹配方法、HU不变矩匹配方法、SIFT特征匹配方法和ORB特征匹配方法分别进行了不同带速、尺度、旋转角度条件下的煤矸石匹配试验,结果表明:本方法的匹配率为98.2%,匹配时间为141 ms,具有匹配率高、实时性好以及鲁棒性强等特点,能够满足煤矸石识别图像与分拣图像高效精准匹配的要求。展开更多
基金the National Hi-tech Research and Development Program of China for its financial support(No.2006AA04Z208).
文摘After a coal mine disaster,especially a gas and coal dust explosion,the space-restricted and unstructured underground terrain and explosive gas require coal mine rescue robots with good obstacle-surmounting performance and explosion-proof capability. For this type of environment,we designed a mobile platform for a rocker-type coal mine rescue robot with four independent drive wheels.The composition and operational principles of the mobile platform are introduced,we discuss the flameproof design of the rocker assembly,as well as the operational principles and mechanical structure of the bevel gear differential and the main parameters are provided.Motion simulation of the differential function and condition of the robot running on virtual,uneven terrain is carried out with ADAMS.The simulation results show that the differential device can maintain the main body of the robot at an average angle between two rockers.The robot model has good operating performance.Experiments on terrain adaptability and surmounting obstacle performance of the robot prototype have been carried out.The results indicate that the prototype has good terrain adaptability and strong obstacle-surmounting performance.
基金Project(2012AA041504)supported by the National High-Tech Research and Development Program of ChinaProject(KYLX15_1418)supported by the 2015 Annual General University Graduate Research and Innovation Program of Jiangsu Province,ChinaProject supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD),China
文摘A new explosion-proof walking system was designed for the coal mine rescue robot(CMRR) by optimizing the mechanical structure and control algorithm. The mechanical structure innovation lies mainly in the dual-motor drive tracked unit used, which showed high dynamic performance compared with the conventional tracked unit. The control algorithm, developed based on decision trees and neural networking, facilitates autonomous switching between "Velocity-driven Mode" and "Torquedriven Mode". To verify the feasibility and effectiveness of the control strategy, we built a self-designed test platform and used it to debug the control program; we then made a robot prototype and conducted further experiments on single-step, ramp, and rubble terrains. The results show that the proposed walking system has excellent dynamic performance and the control strategy is very efficient, suggesting that a robot with this type of explosion-proof walking system can be successfully applied in Chinese coal mines.
文摘With the long-term use of coal bunker, a certain amount of sticking objects will beformed on its wall, and coal mine clearing robot can replace man in clearing the bunker wall.Also, since it equip with an explosion-proof camera, the worker can determine the operationby observing the well-head monitor.Moreover, it cannot work unless it is placed in positionand supported stably, and it has three degrees of freedom: rotating, stretching, and shovelcoal.It is driven by the hydraulic and controlled by PLC.The underground coal mine clearingrobot changs the traditional clearing methods, man does not have to enter the bunker toclear it, which ensures the production safety of coal transportation.
文摘针对煤矸石分拣机器人分拣煤矸石时,带式输送机输送带打滑、跑偏以及带速波动造成的目标煤矸石位姿变化,从而导致抓取失败或空抓漏抓等问题,提出了一种改进的ORB-FLANN (Oriented FAST and Rotated BRIEF-Fast Library for Approximate Nearest Neighbors)煤矸石识别图像与分拣图像高效匹配方法。提出改进ORB的特征点检测方法对煤矸石识别图像与分拣图像进行特征点检测,实现快速检测图像特征点;提出改进FLANN匹配算法对图像特征点进行匹配,实现煤矸石识别图像与分拣图像高效匹配。针对传统ORB方法对煤矸石图像特征检测时间长、重复率低问题,提出了改进ORB特征检测方法,提高了图像特征点检测速度和重复率;针对传统FLANN匹配方法对煤矸石图像匹配精确率低问题,提出了融合PROSAC算法的改进FLANN匹配方法,剔除错误特征匹配点对,提高了图像匹配的精确率。在自主研发的双机械臂桁架式煤矸石分拣机器人试验平台上应用文中方法、SURF特征匹配方法、HU不变矩匹配方法、SIFT特征匹配方法和ORB特征匹配方法分别进行了不同带速、尺度、旋转角度条件下的煤矸石匹配试验,结果表明:本方法的匹配率为98.2%,匹配时间为141 ms,具有匹配率高、实时性好以及鲁棒性强等特点,能够满足煤矸石识别图像与分拣图像高效精准匹配的要求。
