scholarly journals A Novel Step Optimal Path Planning Algorithm for the Spherical Mobile Robot Based on Fuzzy Control

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 1394-1405 ◽  
Author(s):  
Jian Guo ◽  
Chunying Li ◽  
Shuxiang Guo
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Mobile Robot ◽  
Optimal Path ◽  
Optimal Path Planning ◽  
Planning Algorithm ◽  
Spherical Mobile Robot ◽  
Path Planning Algorithm

Fast and Optimal Path Planning Algorithm (FAOPPA) for a Mobile Robot

2019 ◽  
Vol 106 (2) ◽  
pp. 577-592 ◽  
Author(s):  
Patience I. Adamu ◽  
Hilary I. Okagbue ◽  
Pelumi E. Oguntunde
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimal Path ◽  
Optimal Path Planning ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Optimal Collision-Free Path Planning for an Autonomous Multi-Wheeled Combat Vehicle

2017 ◽  
Author(s):  
Amr Mohamed ◽  
Moustafa El-Gindy ◽  
Jing Ren ◽  
Haoxiang Lang
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Vehicle Dynamics ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Vehicle Model ◽  
Optimal Path Planning ◽  
Combat Vehicle ◽  
Planning Algorithm ◽  
Path Planning Algorithm

This paper presents an optimal collision-free path planning algorithm of an autonomous multi-wheeled combat vehicle using optimal control theory and artificial potential field function (APF). The optimal path of the autonomous vehicle between a given starting and goal points is generated by an optimal path planning algorithm. The cost function of the path planning is solved together with vehicle dynamics equations to satisfy the vehicle dynamics constraints and the boundary conditions. For this purpose, a simplified four-axle bicycle model of the actual vehicle considering the vehicle body lateral and yaw dynamics while neglecting roll dynamics is used. The obstacle avoidance technique is mathematically modeled based on the proposed sigmoid function as the artificial potential field method. This potential function is assigned to each obstacle as a repulsive potential field. The inclusion of these potential fields results in a new APF which controls the steering angle of the autonomous vehicle to reach the goal point. A full nonlinear multi-wheeled combat vehicle model in TruckSim software is used for validation. This is done by importing the generated optimal path data from the introduced optimal path planning MATLAB algorithm and comparing lateral acceleration, yaw rate and curvature at different speeds (9 km/h, 28 km/h) for both simplified and TruckSim vehicle model. The simulation results show that the obtained optimal path for the autonomous multi-wheeled combat vehicle satisfies all vehicle dynamics constraints and successfully validated with TruckSim vehicle model.

scholarly journals Development of a Hybrid Path Planning Algorithm and a Bio-Inspired Control for an Omni-Wheel Mobile Robot

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4258 ◽  
Author(s):  
Changwon Kim ◽  
Junho Suh ◽  
Je-Heon Han
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Motion Control ◽  
Control Structure ◽  
Optimal Path ◽  
Tracking Task ◽  
Motion Controller ◽  
Planning Algorithm ◽  
Omni Wheel ◽  
Path Planning Algorithm

This research presents a control structure for an omni-wheel mobile robot (OWMR). The control structure includes the path planning module and the motion control module. In order to secure the robustness and fast control performance required in the operating environment of OWMR, a bio-inspired control method, brain limbic system (BLS)-based control, was applied. Based on the derived OWMR kinematic model, a motion controller was designed. Additionally, an optimal path planning module is suggested by combining the advantages of A* algorithm and the fuzzy analytic hierarchy process (FAHP). In order to verify the performance of the proposed motion control strategy and path planning algorithm, numerical simulations were conducted. Through a point-to-point movement task, circular path tracking task, and randomly moving target tracking task, it was confirmed that the suggesting motion controller is superior to the existing controllers, such as PID. In addition, A*–FAHP was applied to the OWMR to verify the performance of the proposed path planning algorithm, and it was simulated based on the static warehouse environment, dynamic warehouse environment, and autonomous ballet parking scenarios. The simulation results demonstrated that the proposed algorithm generates the optimal path in a short time without collision with stop and moving obstacles.

scholarly journals Study of Double-Weighted Graph Model and Optimal Path Planning for Tourist Scenic Area Oriented Intelligent Tour Guide

2014 ◽  
Vol II-4 ◽  
pp. 65-70
Author(s):  
Y. Shi ◽  
Y. Long ◽  
X. L. Wi
Keyword(s):  
Path Planning ◽  
Model Building ◽  
Single Point ◽  
Optimal Path ◽  
Graph Model ◽  
Structural Features ◽  
Optimal Path Planning ◽  
Proposed Model ◽  
Planning Algorithm ◽  
Path Planning Algorithm

When tourists visiting multiple tourist scenic spots, the travel line is usually the most effective road network according to the actual tour process, and maybe the travel line is different from planned travel line. For in the field of navigation, a proposed travel line is normally generated automatically by path planning algorithm, considering the scenic spots' positions and road networks. But when a scenic spot have a certain area and have multiple entrances or exits, the traditional described mechanism of single point coordinates is difficult to reflect these own structural features. In order to solve this problem, this paper focuses on the influence on the process of path planning caused by scenic spots' own structural features such as multiple entrances or exits, and then proposes a doubleweighted Graph Model, for the weight of both vertexes and edges of proposed Model can be selected dynamically. And then discusses the model building method, and the optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm. Experimental results show that the optimal planned travel line derived from the proposed model and algorithm is more reasonable, and the travelling order and distance would be further optimized.

scholarly journals Intelligent Path Planning Approach for Autonomous Mobile Robot

2021 ◽  
Vol 33 (6) ◽  
pp. 1423-1428
Author(s):  
Ibrahim M. Al-Adwan ◽  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Urban Environment ◽  
Optimal Path ◽  
Autonomous Mobile Robot ◽  
Current Position ◽  
Planning Approach ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Grid Based

This paper presents a new path planning algorithm for an autonomous mobile robot. It is desired that the robot reaches its goal in a known or partially known environment (e.g., a warehouse or an urban environment) and avoids collisions with walls and other obstacles. To this end, a new, efficient, simple, and flexible path finder strategy for the robot is proposed in this paper. With the proposed strategy, the optimal path from the robot’s current position to the goal position is guaranteed. The environment is represented as a grid-based map, which is then divided into a predefined number of subfields to reduce the number of required computations. This leads to a reduction in the load on the controller and allows a real-time response. To evaluate the flexibility and efficiency of the proposed strategy, several tests were simulated with environments of different sizes and obstacle distributions. The experimental results demonstrate the reliability and efficiency of the proposed algorithm.

Sign in / Sign up

Export Citation Format

Share Document