| Summary: | 碩士 === 中原大學 === 機械工程研究所 === 82 === Most of the robotic path plannings rely on users to guide the
robot to move along the working path , or to plan the trace by
a teaching pendant while robot recording the trajectory . These
human teaching methods are applicable to the case of large
number production in a unaltered manufacturing process . When
the tasks are altered constantly as usually occured in flexible
manufacturing system , this routine will become unbearable and
inefficient. This report employs the highly used drawing
software - AutoCAD , to develop a robot path planning tool . At
present, AutoCAD is the most popular drawing tool on the
personal computer , it is very convenient , fully developed ,
and easy to use . So , if applying these capacities on the
robotic trajectory planning and motion control , it will
increase path programming efficiency and provide a convenient ,
functional and economical man-machine interface to users . The
objective is to apply the AutoCAD as the interface between
users and robot . Users need only using a mouse to draw a
working path on the screen and keying in the desired robot
speed , a developed program will automatically convert the
drawing into trajectory commands and feed them into the working
robot . The actual trace of the robot will also be fed back to
the program and shown on the screen as a drawing added on the
origional planned path . Users could immediately observe the
results and decide to accept the response or not, so as to
change the robot moving speed if needed . The experimental
instrument in this work is a rectangular robot driven by
stepping motors . Due to certain limitation of the control
hardware and the open-loop control nature of the robot , the
motion precision is degraded during tracking control . To
improve this deficiency , this report trains a set of neural
networks to predict the tracking error of a given task before
execution ,then compensates the control commands by adjusting
the planned path to increase tracking precision .
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