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Abstract

This paper deals with two control algorithms which utilize learning of their models’ parameters. An adaptive and artificial neural network control techniques are described and compared. Both control algorithms are implemented in MATLAB and Simulink environment, and they are used in the simulation of a postion control of the LWR 4+ manipulator subjected to unknown disturbances. The results, showing the better performance of the artificial neural network controller, are shown. Advantages and disadvantages of both controllers are discussed. The usefulness of the learning algorithms for the control of LWR 4+ robots is discussed. Preliminary experiments dealing with dynamic properties of the two LWR 4+ robots are reported.

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Bibliography

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Authors and Affiliations

Łukasz Woliński
1

  1. Institute of Aeronautics and Applied Mechanics, Warsaw University of Technology, Poland.
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Abstract

The primary importance of the paper is the application of the efficient formulation for the simulation of open-loop lightweight robotic manipulator. The framework employed in the paper makes use of the spatial operator algebra and the associated equations are expressed in joint space. This compact representation of the manipulator dynamics makes it possible to solve the robot forward and inverse dynamics problems in a recursive and fast manner. In the current form, the presented algorithm can be applied for the dynamics simulation of an open-loop chain system possessing any number of joints. Specifically, the formulation has been successfully applied for the analysis of the 7DOF KUKA LWR robot. Results from a number of test cases for the robot demonstrate the verification of the calculations.

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Authors and Affiliations

Łukasz Woliński
Paweł Malczyk

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Abstract

The article describes motion planning of an underwater redundant manipulator with revolute joints moving in a plane under gravity and in the presence of obstacles. The proposed motion planning algorithm is based on minimization of the total energy in overcoming the hydrodynamic as well as dynamic forces acting on the manipulator while moving underwater and at the same time, avoiding both singularities and obstacle. The obstacle is considered as a point object. A recursive Lagrangian dynamics algorithm is formulated for the planar geometry to evaluate joint torques during the motion of serial link redundant manipulator fully submerged underwater. In turn the energy consumed in following a task trajectory is computed. The presence of redundancy in joint space of the manipulator facilitates selecting the optimal sequence of configurations as well as the required joint motion rates with minimum energy consumed among all possible configurations and rates. The effectiveness of the proposed motion planning algorithm is shown by applying it on a 3 degrees-of-freedom planar redundant manipulator fully submerged underwater and avoiding a point obstacle. The results establish that energy spent against overcoming loading resulted from hydrodynamic interactions majorly decides the optimal trajectory to follow in accomplishing an underwater task.
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Authors and Affiliations

Virendra Kumar
1
ORCID: ORCID
Soumen Sen
1
Shibendu Shekhar Roy
2

  1. Robotics and Automation Division, CSIR-Central Mechanical Engineering Research Institute, Durgapur, India
  2. Mechanical Engineering Department, National Institute of Technology, Durgapur, India

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