Optimal Pose Estimation of Robotic Manipulator For Pick And Place Application / Uzair Farrukh

By: Farrukh, UzairContributor(s): Supervisor : Dr. Karam Dad KalluMaterial type: TextTextIslamabad : SMME- NUST; 2022Description: 46p. Soft Copy 30cmSubject(s): Soft Copy MS Robotics and Intelligent Machine EngineeringDDC classification: 629.8 Online resources: Click here to access online
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Thesis Thesis School of Mechanical & Manufacturing Engineering (SMME)
School of Mechanical & Manufacturing Engineering (SMME)
E-Books 629.8 (Browse shelf) Available SMME-TH-737
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This thesis examines how to use robotic manipulator to pick specific object. In order
to attain above objective planning of manipulator as well as grasping point calculations
are studied. The process of calculating grasping pose with respect to target object,the
grasping point essential for successful grasping of object is called grip synthesis.Both analytical and empirical approaches are used to calculate grasping points. While empirical
uses human like strategies, analytical approaches are mainly dependent on geometric,
kinematic, and/or dynamic formulations. The main goal of the thesis is to minimize
joint accelerations. Constrained optimization techniques like genetic algorithm and path
search algorithm are used to find grasping point and minimize joint accelerations to ensure successful grasping of object.A novel hybrid approach is also proposed which used
both genetic algorithm and path search algorithm to find its fitness value. The first
contribution is finding optimal grasping points of regular shaped object by calculating
centroid of object and are near to centroid along minor axis. The second contribution
is to minimize joint accelerations by using optimization techniques of genetic algorithm
and path search algorithm in which global minima’s are found and optimized trajectory
is generated which helps in successful grasps with minimum joints accelerations. Third
is the introduction of novel hybrid approach which uses both genetic algorithm and
pattern search algorithm to find its global minima which is more robust for changing
search space.

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