Mobile Robot Path Planning based on Conformal Geometric Algebra and Teaching-Learning Based Optimization

Hernández-Barragán, Jesús

doi:10.1016/j.ifacol.2018.07.301

Cited by 7 publications

(4 citation statements)

References 17 publications

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“…Compared with PSO, invasive weed optimization (IWO), and biogeography-based optimization (BBO), simulation results showed a better performance for the proposed algorithm. In [31], a conformal geometric algebra and TLBO are proposed for a mobile robot's path planning. First, the robot and the obstacles are considered as conformal spheres.…”

Section: Related Workmentioning

confidence: 99%

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Real-time path planning for autonomous vehicle based on teaching–learning-based optimization

Sabiha

Kamel

Said

et al. 2022

Intel Serv Robotics

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This paper presents an online path planning approach for an autonomous tracked vehicle in a cluttered environment based on teaching–learning-based optimization (TLBO), considering the path smoothness, and the potential collision with the surrounding obstacles. In order to plan an efficient path that allows the vehicle to be autonomously navigated in cluttered environments, the path planning problem is solved as a multi-objective optimization problem. First, the vehicle perception is fully achieved by means of inertial measurement unit (IMU), wheels odometry, and light detection and ranging (LiDAR). In order to compensate the sensors drift to achieve more reliable data and improve the localization estimation and corrections, data fusion between the outputs of wheels odometry, LiDAR, and IMU is made through extended Kalman filter (EKF). Then, TLBO is proposed and applied to determine the optimum online path, where the objectives are to find the shortest path to reach the target destination, and to maximize the path smoothness, while avoiding the surrounding obstacles, and taking into account the vehicle dynamic and algebraic constraints. To check the performance of the proposed TLBO algorithm, it is compared in simulation to genetic algorithm (GA), particle swarm optimization (PSO), and a hybrid GA–PSO algorithm. Finally, real-time experiments based on robot operating system (ROS) implementation are conducted to validate the effectiveness of the proposed path planning algorithm.

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Section: Related Workmentioning

confidence: 99%

“…TLBO is widely applied in path planning of robotic manipulators [27,28]. However, very few works focused on applying TLBO for UGV path planning [31][32][33]; and 4. Most of the existing TLBO techniques have not yet been validated experimentally.…”

Section: Related Workmentioning

confidence: 99%

Real-time path planning for autonomous vehicle based on teaching–learning-based optimization

Sabiha

Kamel

Said

et al. 2022

Intel Serv Robotics

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“…In [26], a conformal geometric algebra and TLBO are proposed for path planning of mobile robot avoiding all the possible obstacles in the navigation task. The proposed method is conformal spheres to represent the mobile robot and the obstacles.…”

Section: Introductionmentioning

confidence: 99%

“…However, their main demerit is the selection and tuning of the algorithm-specific parameters; and • The TLBO is widely applied in the path planning of robotic manipulators [22][23]. However, very few works focused on applying TLBO for UGV path planning [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Path Planning Algorithm Based on Teaching-Learning-Based-Optimization for an Autonomous Vehicle

Desoky¹,

Kamel²,

Said³

et al. 2022

Communications

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This study provides a teaching-learning-based optimization (TLBO) path planning method for an autonomous vehicle in a cluttered environment, which takes into account path smoothness and the possibility of collision with nearby obstacles. The path planning problem is tackled as a multiobjective optimization in order to plan an efficient path that allows the vehicle to travel autonomously in crowded settings. The TLBO algorithm is used to find the ideal path, with the goals of finding the shortest path to the target site and maximizing path smoothness, while avoiding obstacles and taking into account the vehicle's dynamic and algebraic properties.

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Trajectory Optimization of an Industrial Robot Using Teaching–Learning-Based Optimization

Shinde¹,

Pawar²

2023

Advanced Engineering Optimization Through Intelligent Techniques

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Mobile Robot Path Planning based on Conformal Geometric Algebra and Teaching-Learning Based Optimization

Cited by 7 publications

References 17 publications

Real-time path planning for autonomous vehicle based on teaching–learning-based optimization

Real-time path planning for autonomous vehicle based on teaching–learning-based optimization

Path Planning Algorithm Based on Teaching-Learning-Based-Optimization for an Autonomous Vehicle

Trajectory Optimization of an Industrial Robot Using Teaching–Learning-Based Optimization

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