Path Planning of Mobile Robot Agent Using Heuristic Based Integrated Hybrid Algorithm

2014 ◽  
Vol 984-985 ◽  
pp. 1229-1234
Author(s):  
K. Sudhagar ◽  
M. Bala Subramanian ◽  
G. Rajarajeswari
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimal Path ◽  
Dynamic Environment ◽  
Test Bed ◽  
Unknown Environment ◽  
Optimal Path Planning ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Behavioural Aspects

Optimal path planning is considered to be the key area, which gives much attention to researchers in the field of robotic research community. In this paper, a comprehensive simulation study was made on applying heuristic based optimal path planning algorithm of a mobile robot agent in an dynamic environment. This study aims on the behavioural aspects, exploration and navigational aspects along with optimal path analysis of a mobile robot agent. The behaviour selection of a mobile robot agent is considered to be the key challenge for designing a control architecture system, in which it is highly suitable for dynamically changing environment. A mobile robot agent participating for mission critical application will explore into an known environment without any discrepancy, but exploring into an unknown environment will be a challenging criterion, considering its constraints such as time, cost, energy, exploration distance etc., This paper aims on navigational study of the mobile robot agent participating in dynamically changing environments, using heuristic approach. The System evaluation is validated using Graphical User Interface (GUI) based test-bed for Robots called RoboSim and the efficiency of the system is measured, via Simulation Results. Simulation results prove that applying A* algorithm in an unknown environment explores much faster than other path planning algorithms.

The Study on Mobile Robot Path Planning Based on Frog Leaping Algorithm

2012 ◽  
Vol 490-495 ◽  
pp. 808-812
Author(s):  
Zheng Ran Zhang ◽  
Ji Ying Yin
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimization Problem ◽  
Optimal Path ◽  
Robot Path Planning ◽  
Unknown Environment ◽  
Simulation Results ◽  
Robot Path

We have proposed a method of robot path planning in a partially unknown environment in this paper. We regard the problem of robot path planning as an optimization problem and solve it with the SFL algorithm. The position of globally best frog in each iterative is selected, and reached by the robot in sequence. The obstacles are detected by the robot sensors are applied to update the information of the environment. The optimal path is generated until the robot reaches its target. The simulation results validate the feasibility of the proposed method.

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

scholarly journals Research on optimal path planning of indoor robot based on wireless sensor

2021 ◽  
Vol 2093 (1) ◽  
pp. 012009
Author(s):  
Shouwen Wang
Keyword(s):  
Path Planning ◽  
Wireless Sensors ◽  
Optimal Path ◽  
Wireless Sensor ◽  
Target Point ◽  
Optimal Path Planning ◽  
Work Tasks ◽  
Planning Algorithm ◽  
Simulation Results ◽  
Path Planning Algorithm

Abstract Based on the work tasks and positioning characteristics of indoor robots, the environment is divided into grids, and wireless sensors are used to detect obstacles, and the density of obstacles in each grid is given. At the same time, the path planning algorithm is combined to realize the optimal path planning of indoor robot. The simulation results show that the wireless sensor network can realize the obstacle density detection, so that the robot can achieve fast optimal path planning and reach the target point.

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 Sensor-network-based navigation of delivery robot for baggage handling in international airport

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142094473
Author(s):  
Kefei Shen ◽  
Chen Li ◽  
Difei Xu ◽  
Weihong Wu ◽  
He Wan
Keyword(s):  
Path Planning ◽  
Time Window ◽  
Optimal Path ◽  
Automated Guided Vehicles ◽  
Ultra Wideband ◽  
Maintenance Cost ◽  
Optimal Path Planning ◽  
International Airport ◽  
Baggage Handling ◽  
Planning Algorithm

Automated guided vehicles (AGVs) have been regarded as a promising means for the future delivery industry by many logistic companies. Several AGV-based delivery systems have been proposed, but they generally have drawbacks in delivering and locating baggage by magnet line, such as the high maintenance cost, and it is hard to change the trajectory of AGV. This article considers using multi-AGVs as delivery robots to coordinate and sort baggage in the large international airport. This system has the merit of enlarging the accuracy of baggage sorting and delivering. Due to the inaccurate transportation efficiency, a time-dependent stochastic baggage delivery system is proposed and a stochastic model is constructed to characterize the running priority and optimal path planning for multi-AGVs according to the flight information. In the proposed system, ultra-wideband technology is applied to realize precisely positioning and navigation for multi-AGVs in the baggage distribution center. Furthermore, the optimal path planning algorithm based on time-window rules and rapidly exploring random tree algorithm is considered to avoid collision and maneuverability constraints and to determine whether the running path for each AGV is feasible and optimal. Computer simulations are conducted to demonstrate the performance of the proposed method.

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