Design of Motion Control for Mobile Robot Manipulator

Widhiada, W.; Santhiarsa, I. G. N.; Partha, Cok Gede Indra

doi:10.18178/ijmerr.9.11.1509-1514

Cited by 7 publications

(2 citation statements)

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“…Due to its nonholonomic nature, the mobile robot cannot move in all directions [25][26][27]. The DD mobile robot's motion is determined by the following kinematic equations:…”

Section: System Modelingmentioning

confidence: 99%

Redundancy Resolution of a Mobile Manipulator Using Learning Based Algorithm

Tolossa,

Gupta,

Orlando

et al. 2024

Preprint

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A learning-based strategy for the trajectory tracking of redundant mobile manipulators (MM) was presented in this study. A five-degrees-of-freedom (DOF) manipulator is mounted on the differential drive (DD) mobile robot. The advantage of using a redundant system is to avoid joint limits, obstacles and singularities towards desired trajectory tracking. The proposed approach is based on Kohonen Self-Organizing Map (KSOM) enhanced a weighted least norm (WLN) matrix algorithm. This approach is the recommended neural network for inverse kinemat-ics solutions because of its stability, preserved topology, and capacity to optimize the joint space trajectory while producing a smooth minimal joint angle. A proposed method for redundancy resolution in MM has been simulated using MATLAB simulation code and the Gazebo real-time simulation pysical environment. The simulation results are evaluated with the joint limit method of redundancy resolution and other existing controllers for verification purpose. The conventional method of redundancy resolution is local optimum and infeasible for the end-effector motion in the entire workspace. The KSOM uses different steps of error correction that improve the system’s performance as well as ensure the global asymptotical stability of the system.

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“…Due to its nonholonomic nature, the mobile robot cannot move in all directions [25][26][27]. The DD mobile robot's motion is determined by the following kinematic equations:…”

Section: System Modelingmentioning

confidence: 99%

Redundancy Resolution of a Mobile Manipulator Using Learning Based Algorithm

Tolossa,

Gupta,

Orlando

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…al. [9] focused on PID control of Mobile Robot, Paakönen [10] published a Master Thesis on Cloud-based Remote Control of Autonomous Mobile Robots in industrial environments, Oltean [11] conducted a study on low-cost Mobile Robot Platform, Sichkar et. al.…”

Section: Introductionmentioning

confidence: 99%

Topology Optimization of Mobile Transportation Robot

DEMİR

Sucuoğlu

Böğrekçi

et al. 2021

International Journal of 3D Printing Technologies and Digital Industry

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The main aim of this study was to decrease the weight of mobile transportation robot and to check the optimized shape using topology optimization and structural analysis. The analyses were applied using CAE (Computer Aided Engineering) Software with the methods of topology optimization and structural analysis. In the topology optimization process, the preserved areas were defined for connection and fixing areas. The aim was to decrease the weight of robot structure and lower the energy consumption of the robotic system. After topology optimization, the structural strength analysis was applied to the new optimized structure to check about the strength. The weight of the structure was decreased with the ratio of 20%. In addition to this, the structural strength of the robot was observed similar to the original body with the factor of safety value as three.

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Redundancy resolution of a mobile manipulator using the KSOM based learning algorithm

Deme Tolossa,

Gupta,

Orlando

et al. 2024

Int J Intell Robot Appl

View full text Add to dashboard Cite

A learning-based strategy for the trajectory tracking of redundant mobile manipulators (MM) was presented in this study. A five-degrees-offreedom (DOF) manipulator is mounted on the differential drive (DD) mobile robot. The advantage of using a redundant system is to avoid joint limits, obstacles and singularities towards desired trajectory tracking. The proposed approach is based on Kohonen Self-Organizing Map (KSOM) enhanced a weighted least norm (WLN) matrix algorithm. This approach is the recommended neural network for inverse kinematics solutions because of its stability, preserved topology, and capacity to optimize the joint space trajectory while producing a smooth minimal joint angle. A proposed method for redundancy resolution in MM has been simulated using MATLAB simulation code and the Gazebo real-time simulation pysical environment. The simulation results are evaluated with the joint limit method of redundancy resolution and other existing controllers for verification purpose. The conventional method of redundancy resolution is local optimum and infeasible for the end-effector motion in the entire workspace. The KSOM uses different steps of error correction that improve the system's performance as well as ensure the global asymptotical stability of the system.

show abstract

Design of Motion Control for Mobile Robot Manipulator

Cited by 7 publications

References 0 publications

Redundancy Resolution of a Mobile Manipulator Using Learning Based Algorithm

Redundancy Resolution of a Mobile Manipulator Using Learning Based Algorithm

Topology Optimization of Mobile Transportation Robot

Redundancy resolution of a mobile manipulator using the KSOM based learning algorithm

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