A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel indep...A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel independent steering system was capable of providing a low-speed steering control of the robot based on Ackerman steering geometry.The proportional-integral-derivative(PID)algorithm was used in the laser navigation control system.The Otsu algorithm and the elliptic template method were used for the automatic recognition of ripe tomatoes,and obstacle avoidance strategies were proposed based on the C-space method.The maximum average absolute error between the set angle and the actual angle was about 0.14°,and the maximum standard deviation was about 0.04°.The laser navigation system was able to rapidly and accurately track the path,with the deviation being less than 8 cm.The load bearing capacity of the mechanical arm was about 1.5 kg.The success rate of the binocular vision system in the recognition of ripe tomatoes was 99.3%.When the distance was less than 600 mm,the positioning error was less than 10 mm.The time needed for recognition of ripe tomatoes and pitching was about 15 s per tomato,with a success rate of about 86%.This study provides some insights into the development and application of tomato harvesting robot used in the greenhouse.展开更多
基金supported by the National 863 planning project of China-digital design and intelligent control technology of agricultural facilities equipment(2013AA102406)the Beijing municipal science and technology project(Z161100004916118).
文摘A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel independent steering system was capable of providing a low-speed steering control of the robot based on Ackerman steering geometry.The proportional-integral-derivative(PID)algorithm was used in the laser navigation control system.The Otsu algorithm and the elliptic template method were used for the automatic recognition of ripe tomatoes,and obstacle avoidance strategies were proposed based on the C-space method.The maximum average absolute error between the set angle and the actual angle was about 0.14°,and the maximum standard deviation was about 0.04°.The laser navigation system was able to rapidly and accurately track the path,with the deviation being less than 8 cm.The load bearing capacity of the mechanical arm was about 1.5 kg.The success rate of the binocular vision system in the recognition of ripe tomatoes was 99.3%.When the distance was less than 600 mm,the positioning error was less than 10 mm.The time needed for recognition of ripe tomatoes and pitching was about 15 s per tomato,with a success rate of about 86%.This study provides some insights into the development and application of tomato harvesting robot used in the greenhouse.
