To elucidate, the new teaching system is divided into three parts, specifically, hardware, software, and computation (Figure 1), as listed below.Figure 1.System overview.2.1. Hardware2.1.1. Teach PenA comparison between the traditional teach pendant and teach pen is shown in Figure 2. The teach pendant (Figure 2a) controls the 6-DoF of the robotic-arm endpoint by twelve + and �C buttons, which is not intuitive or convenient. By contrast, the teach pen (Figure 2b) resembles the number ��7�� and has three active markers, three lock buttons, and one non-lock button. The three markers collect data related to the pen pose and coordinates, and calculate the pen tip coordinates and the pose of the rigid arm body using a proposed algorithm.
Concurrently, the signals from the buttons are processed using the Arduino MCU development kit, which controls the opening and closing of the claw.Figure 2.(a) The traditional teach pendant; (b) the proposed teach pen.2.1.2. The Motion Capture SystemVZ4000, an optical 3D motion tracker developed by PhoeniX Technologies Inc. (New Taipei, Taiwan) was employed to process the coordinates collected by the three markers on the pen and the two active markers on the operator arm to a measurement accuracy of 0.6 mm and a sample frequency of 2 KHz. The data collected by the optical markers on the pen and the opera
In the framework of the European FP7 project Clever Robots for Crops��CROPS [1] several highly configurable and modular demonstrators are currently under development for robotic harvesting of high value greenhouse vegetables and fruits in orchards.
One of the key issues in automated fruit harvesting is the localization of the fruits on the plant by means of a sensor system. The desired situation is to detect and localize close to 100% of all ripe fruits on the plant. For robotic harvesting of sweet-pepper fruits in a greenhouse a computer Anacetrapib vision system is a possible approach for fruit detection. Due to the structure of the production system, images could then be taken using a device that is placed between the plant rows. In many cases however, fruits will not be completely visible because leaves or branches will hang in front of fruits or individual fruits are not clearly visible because they are often growing closely together in clusters. Publications from [2] or [3] confirm that the main problem in automated fruit harvesting is the visibility of the fruits in the crop.
However, little information about fruit visibility is available so far from literature, and only a few authors, for example [4,5], give quantitative numbers.In other studies multiple camera viewpoints were also used to acquire images of the crop. In the research of [6] images of cucumber plants were taken with a linear displacement of 0.33 m. Thereby every plant was visible in three subsequent images.