Grid-Based Mobile Robot Path Planning Using Aging-Based Ant Colony Optimization Algorithm in Static and Dynamic Environments

Ajeil, Fatin Hassan; Ibraheem, Ibraheem Kasim; Azar, Ahmad Taher; Humaidi, Amjad J.

doi:10.3390/s20071880

Cited by 131 publications

(64 citation statements)

References 25 publications

(33 reference statements)

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“…In future work, this approach can be extended to nest more than two LESOs, and nonlinear ESOs could also be used and their performance investigated for multi-input-multi-output (MIMO) systems. Finally, several real-world nonlinear models can be used to show the performance of the N-ADRC as given in [45][46][47][48][49][50][51][52][53].…”

Section: Discussionmentioning

confidence: 99%

Novel Active Disturbance Rejection Control Based on Nested Linear Extended State Observers

Abdul-Adheem¹,

Ibraheem²

2020

Applied Sciences

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In this paper, a Novel Active Disturbance Rejection Control (N-ADRC) strategy is proposed that replaces the Linear Extended State Observer (LESO) used in Conventional ADRC (C-ADRC) with a nested LESO. In the nested LESO, the inner-loop LESO actively estimates and eliminates the generalized disturbance. Increasing the bandwidth improves the estimation accuracy which may tolerate noise and conflict with H/W limitations and the sampling frequency of the system. Therefore, an alternative scenario is offered without increasing the bandwidth of the inner-loop LESO provided that the rate of change of the generalized disturbance estimation error is upper bounded. This was achieved by the placing of an outer-loop LESO in parallel with the inner one that estimates and eliminates the remaining generalized disturbance originating from the inner-loop LESO due to bandwidth limitations. The stability of LESO and nested LESO was investigated using Lyapunov stability analysis. Simulations on uncertain nonlinear single-input-single-output (SISO) system with time-varying exogenous disturbance revealed that the proposed nested LESO could successfully deal with a generalized disturbance in both noisy and noise-free environments, where the Integral Time Absolute Error (ITAE) of the tracking error for the nested LESO was reduced by 69.87% from that of the LESO.

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Section: Discussionmentioning

confidence: 99%

Novel Active Disturbance Rejection Control Based on Nested Linear Extended State Observers

Abdul-Adheem¹,

Ibraheem²

2020

Applied Sciences

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“…These algorithms include the shortest graph-based path algorithm known as A *, the artificial potential field algorithm, sequential quadratic programming and so on. Additionally, an approach based on ant-colony behavior is often used [ 11 , 17 ]. In recent years, due to the progress of neural networks, the deep learning and specifically deep reinforcement learning approaches [ 18 , 19 ] are becoming more and more popular.…”

Section: Introductionmentioning

confidence: 99%

2D Optimal Trajectory Planning Problem in Threat Environment for UUV with Non-Uniform Radiation Pattern

Galyaev

Lysenko

Yakhno

2021

Sensors

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Path planning is necessary in many applications using unmanned underwater vehicles (UUVs). The main class of tasks is the planning of safe routes with minimal energy costs and/or minimal levels of emitted physical and information signals. Since the action planner is on board the UUV, the main focus is on methods and algorithms that allow it to build reference trajectories while minimizing the number of calculations. The study is devoted to the problem of the optimal route planning for a UUV with a non-uniform radiation pattern. The problem is stated in the form of two point variational problem for which necessary and sufficient optimality conditions are proved. Particular attention is paid to cases where optimality conditions are not met. These cases are directly related to found specific forms of a radiation pattern. Sufficient optimality conditions are extended on the class of two-link and multi-link motion paths. Software tools have been developed and computer simulations have been performed for various types of radiation patterns.

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“…Path planning is recognized as a key technique of AUVs. Traditional path planning algorithms include the A* algorithm [4], the Rapidly exploring Random Tree (RRT) [5] algorithm, the D* algorithm [6], the Dijkstra algorithm [7,8], the Ant Colony Optimization (ACO) algorithm [9,10,11] and the Artificial Potential Field (APF) algorithm [12,13]. The A*, D*, Dijkstra and ACO algorithms are path planning methods based on graph theory.…”

Section: Introductionmentioning

confidence: 99%

Improved Quantum Particle Swarm Optimization Algorithm for Offline Path Planning in AUVs

Wang

Liu

et al. 2020

IEEE Access

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This paper proposes an offline path planning method based on the Improved Quantum Particle Swarm Optimization (IQPSO) algorithm for Autonomous Underwater Vehicles (AUVs) in the underwater environment. The spherical modelling method is adopted to represent irregular underwater obstacles as spheres with a specified radius. Then, the IQPSO algorithm is developed to solve the problem of the limitations of the convergence and optimization ability of the traditional Quantum Particle Swarm Optimization (QPSO) algorithm and to identify the best path for AUVs. In this algorithm, to satisfy the three factors of path safety, path length and angle change of the path point, the fitness function is constructed to achieve multi-objective optimization. A smooth path is designed using the cubic spline interpolation algorithm. Different scenes or the same scene with different obstacles are designed to verify the effectiveness of the algorithm. The simulation results show that compared with PSO algorithm, QPSO algorithm, EGA algorithm and DENPSO algorithm, the path generated by IQPSO algorithm in various scenes is shorter, smoother and more stable. INDEX TERMS AUV, improved QPSO algorithm, multi-objective optimization, path planning.

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Grid-Based Mobile Robot Path Planning Using Aging-Based Ant Colony Optimization Algorithm in Static and Dynamic Environments

Cited by 131 publications

References 25 publications

Novel Active Disturbance Rejection Control Based on Nested Linear Extended State Observers

Novel Active Disturbance Rejection Control Based on Nested Linear Extended State Observers

2D Optimal Trajectory Planning Problem in Threat Environment for UUV with Non-Uniform Radiation Pattern

Improved Quantum Particle Swarm Optimization Algorithm for Offline Path Planning in AUVs

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