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Synthesis of continuous whole-body motion in hexapod robot for humanitarian demining
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIn the context of control, the motion of a legged robot is very challenging compared
with traditional fixed manipulator. Recently, many researches have been conducted
to control the motion of legged robot with different techniques. On the other hand,
manipulation tasks have been addressed in many applications. These researches solved
either the mobility or the manipulation problems, but integrating both properties
in one system is still not available. In this thesis, a control algorithm is presented
to control both locomotion and manipulation in a six legged robot. Landmines
detection process is considered as a case study of this project to accelerate the mine
detection operation by performing both walking and scanning simultaneously. In
order to qualify the robot to perform more tasks in addition to the walking task,
the joint redundancy of the robot is exploited optimally. The tasks are arranged
according to their importance to high level of priority and low level of priority. A new
task priority redundancy resolution technique is developed to overcome the effect
of the algorithmic singularities and the kinematic singularity. The computational
aspects of the solution are also considered in view of a real-time implementation.
Due to the dynamic changes in the size of the robot motion space, the algorithm
has the ability to make a trade-off between the number of achieved tasks and the
imposed constraints. Furthermore, an appropriate hierarchy is imposed in order
to ensure an accurate decoupling between the executed tasks. The dynamic effect
of the arm on the overall performance of the robot is attenuated by reducing the
optimisation variables. The effectiveness of the method is evaluated on a Computer
Aided Design (CAD) model and the simulations of the whole operation are conducted
using MATLAB and SimMechanics.Iraqi ministry of Higher Education and Scientific Researc
A control structure for ambidextrous robot arm based on Multiple Adaptive Neuro‐Fuzzy Inference System
Abstract This paper presents the novel design of an ambidextrous robot arm that offers double range of motion as compared to dexterous arms. The arm is unique in terms of design (ambidextrous feature), actuation (use of two different actuators simultaneously: Pneumatic Artificial Muscle (PAM) and Electric Motors)) and control (combined use of Proportional Integral Derivative (PID) with Neural Network (NN) and Multiple Adaptive Neuro‐fuzzy Inference System (MANFIS) controller with selector block). In terms of ambidextrous robot arm control, a solution based on forward kinematic and inverse kinematic approach is presented, and results are verified using the derived equation in MATLAB. Since solving inverse kinematics analytically is difficult, Adaptive Neuro Fuzzy Inference system (ANFIS) is developed using ANFIS MATLAB toolbox. When generic ANFIS failed to produce satisfactory results due to ambidextrous feature of the arm, MANFIS with a selector block is proposed. The efficiency of the ambidextrous arm has been tested by comparing its performance with a conventional robot arm. The results obtained from experiments proved the efficiency of the ambidextrous arm when compared with conventional arm in terms of power consumption and stability