Stabilization of wheeled mobile robot by social spider algorithm based PID controller

Khan, Huma; Khatoon, Shahida; Gaur, Prerna

doi:10.1007/s41870-023-01438-w

Int. j. inf. tecnol.

2023

DOI: 10.1007/s41870-023-01438-w

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Stabilization of wheeled mobile robot by social spider algorithm based PID controller

Huma Khan,

Shahida Khatoon,

Prerna Gaur

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2024

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Cited by 3 publications

References 25 publications

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An omnidirectional mecanum wheel automated guided vehicle control using hybrid modified A* algorithm

Bhargava,

Suhaib,

Singholi

2024

Robotica

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This paper presents Hybrid Modified A* (HMA*) algorithm which is used to control an omnidirectional mecanum wheel automated guided vehicle (AGV). HMA* employs Modified A* and PSO to determine the best AGV path. The HMA* overcomes the A* technique’s drawbacks, including a large number of nodes, imprecise trajectories, long calculation times, and expensive path initialization. Repetitive point removal refines Modified A*’s path to locate more important nodes. Real-time hardware control experiments and extensive simulations using Matlab software prove the HMA* technique works well. To evaluate the practicability and efficiency of HMA* in route planning and control for AGVs, various algorithms are introduced like A*, Probabilistic Roadmap (PRM), Rapidly-exploring Random Tree (RRT), and bidirectional RRT (Bi-RRT). Simulations and real-time testing show that HMA* path planning algorithm reduces AGV running time and path length compared to the other algorithms. The HMA* algorithm shows promising results, providing an enhancement and outperforming A*, PRM, RRT, and Bi-RRT in the average length of the path by 12.08%, 10.26%, 7.82%, and 4.69%, and in average motion time by 21.88%, 14.84%, 12.62%, and 8.23%, respectively. With an average deviation of 4.34% in path length and 3% in motion time between simulation and experiments, HMA* closely approximates real-world conditions. Thus, the proposed HMA* algorithm is ideal for omnidirectional mecanum wheel AGV’s static as well as dynamic movements, making it a reliable and efficient alternative for sophisticated AGV control systems.

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An omnidirectional mecanum wheel automated guided vehicle control using hybrid modified A* algorithm

Bhargava,

Suhaib,

Singholi

2024

Robotica

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Intelligent controller design of an autonomous system using a social spider optimizer for path navigation and obstacle avoidance

Hasan,

Khan,

Khatoon

et al. 2024

Automatika

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Optimized trajectory tracking control with disturbance resistance for wheeled mobile robot

Chai,

Zhang,

Tan

2024

Transactions of the Institute of Measurement and Control

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When unavoidable disturbances exist in practical applications, the unicycle wheeled mobile robot (WMR) with non-holonomic constraint is challenging to be accurately controlled in finite time. An optimized dual closed-loop strategy is proposed in this paper to solve the trajectory tracking control problem of the unicycle WMR. The control strategy with fast time convergence and anti-disturbance properties consists of kinematic and dynamics controllers and an optimization algorithm. The kinematic controller is designed with an improved backstepping method to eliminate the non-holonomic constraints. The robust sliding mode control (SMC) method with fixed-time convergence is used to construct the dynamics controller. The optimization algorithm enhances the performance of the strategy and achieves accurate control. The global convergence and robustness of the strategy are theoretically demonstrated. The effectiveness of the strategy is verified by comparison in simulations.

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Stabilization of wheeled mobile robot by social spider algorithm based PID controller

Cited by 3 publications

References 25 publications

An omnidirectional mecanum wheel automated guided vehicle control using hybrid modified A* algorithm

An omnidirectional mecanum wheel automated guided vehicle control using hybrid modified A* algorithm

Intelligent controller design of an autonomous system using a social spider optimizer for path navigation and obstacle avoidance

Optimized trajectory tracking control with disturbance resistance for wheeled mobile robot

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