NASCIMENTO, F. H. N.; http://lattes.cnpq.br/3903741548185246; NASCIMENTO, Felipe Henrique Neiva do.
Resumo:
This work addresses a kinematic control solution for multiple cooperative manipulators in
a pre defined trajectory with object manipulation, while a depth vision system locates
and tracks an object using Particle Filter. The general objective is to present a solution
for task space control with kinematic control for multiple manipulators, with the ability
to locate and track the position of the manipulated object. To this end, kinematic control
techniques are used with an approach for multiple cooperative robots. Three techniques
for jacobian inverse are used, being them jacobian inverse, pseudo inverse and damped
least squares. The control solutions used for the manipulators are proportional control,
proportional and integral control and proportional feedforward control. These techniques
are implemented in the V-REP simulator and in an experimental enviroment with two
UR5 manipulators. Step response and pre defined trajectory control tests are realized.
For object location and tracking, a Kinect is used in the ROS ambient with PCL. A
technique for localization based on models with particle filter is used. Experiments with
both arms manipulating an object are done, using cooperative manipulators principles
and the kinematic control techniques developed. Both systems are integrated together for
dual arm kinematic control with object localization and tracking. The jacobian inverse
techniques developed are applied with success and a comparison beetween the performance
of the three is done, where it was found that the damped least squares method is the best
method for the rest of the work. The trajectory control is successfully done with the three
controllers, but the steady state error goes to zero only with the proportional feedforward
control. The dual arm manipulation is done with success, but there is a delay in the
communication system, resulting on a steady state error. The model based localization
method developed can locate and track the object during the trajectory but, because a
uncertainty in the experimental enviroment and sensor inaccuracy, the tracking quality is
smaller than expected. Nevertheless, the tracking is done successfully.