A prioritized planning algorithm of trajectory coordination based on time windows for multiple AGVs with delay disturbance

2019 ◽  
Vol 39 (5) ◽  
pp. 753-768 ◽  
Author(s):  
Ruochen Tai ◽  
Jingchuan Wang ◽  
Weidong Chen
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Scheduling Algorithm ◽  
Time Windows ◽  
Previous Method ◽  
Automated Guided Vehicles ◽  
Content Type ◽  
Time Performance ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Purpose In the running of multiple automated guided vehicles (AGVs) in warehouses, delay problems in motions happen unavoidably as there might exist some disabled components of robots, the instability of networks and the interference of people walking. Under this case, robots would not follow the designed paths and the coupled relationship between temporal and space domain for paths is broken. And there is no doubt that other robots are disturbed by the ones where delays happen. Finally, this brings about chaos or even breakdown of the whole system. Therefore, taking the delay disturbance into consideration in the path planning of multiple robots is an issue worthy of attention and research. Design/methodology/approach This paper proposes a prioritized path planning algorithm based on time windows to solve the delay problems of multiple AGVs. The architecture is a unity consisting of three components which are focused on scheduling AGVs under normal operations, delays of AGVs, and recovery of AGVs. In the components of scheduling AGVs under normal operations and recovery, this paper adopts a dynamic routing method based on time windows to ensure the coordination of multiple AGVs and efficient completion of tasks. In the component for scheduling AGVs under delays, a dynamical prioritized local path planning algorithm based on time windows is designed to solve delay problems. The introduced planning principle of time windows would enable the algorithm to plan new solutions of trajectories for multiple AGVs, which could lower the makespan. At the same time, the real-time performance is acceptable based on the planning principle which stipulates the parameters of local time windows to ensure that the computation of the designed algorithm would not be too large. Findings The simulation results demonstrate that the proposed algorithm is more efficient than the state-of-the-art method based on homotopy classes, which aims at solving the delay problems. What is more, it is validated that the proposed algorithm can achieve the acceptable real-time performance for the scheduling in warehousing applications. Originality/value By introducing the planning principle and generating delay space and local adjustable paths, the proposed algorithm in this paper can not only solve the delay problems in real time, but also lower the makespan compared with the previous method. The designed algorithm guarantees the scheduling of multiple AGVs with delay disturbance and enhances the robustness of the scheduling algorithm in multi-AGV system.

On-Line Centralized Path Planning of Multiple Mobile Robots in Dynamic Environments

2012 ◽  
Vol 155-156 ◽  
pp. 1074-1079
Author(s):  
Zi Hui Zhang ◽  
Yue Shan Xiong
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Dynamic Environments ◽  
Characteristic Line ◽  
Multiple Mobile Robots ◽  
Time Performance ◽  
Planning Algorithm ◽  
On Line ◽  
Path Planning Algorithm

To study the path planning problem of multiple mobile robots in dynamic environments, an on-line centralized path planning algorithm is proposed. It is difficult to obtain real-time performance for path planning of multiple robots in dynamic environment. The harmonic potential field for multiple mobile robots is built by using the panel method known in fluid mechanics, which represents the outward normal velocity of each line of a polygonal obstacle as a function of the length of its characteristic line. The simulation results indicate that it is a simple, efficient and effective path planning algorithm for multiple mobile robots in the dynamic environments that the geometries and trajectories of obstacles are known in advance, and can achieve real-time performance.

scholarly journals A Bi-Level Probabilistic Path Planning Algorithm for Multiple Robots with Motion Uncertainty

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Jingchuan Wang ◽  
Ruochen Tai ◽  
Jingwen Xu
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Conflict Avoidance ◽  
System Efficiency ◽  
Multiple Robots ◽  
Time Performance ◽  
Planning Algorithm ◽  
Probabilistic Path Planning ◽  
Simulation Results ◽  
Path Planning Algorithm

For improving the system efficiency when there are motion uncertainties among robots in the warehouse environment, this paper proposes a bi-level probabilistic path planning algorithm. In the proposed algorithm, the map is partitioned into multiple interconnected districts and the architecture of proposed algorithm is composed of topology level and route level generating from above map: in the topology level, the order of passing districts is planned combined with the district crowdedness to achieve the district equilibrium and reduce the influence of robots under motion uncertainty. And in the route level, a MDP method combined with probability of motion uncertainty is proposed to plan path for all robots in each district separately. At the same time, the number of steps for each planning is dependent on the probability to decrease the number of planning. The conflict avoidance is proved, and optimization is discussed for the proposed algorithm. Simulation results show that the proposed algorithm achieves improved system efficiency and also has acceptable real-time performance.

scholarly journals Indoor Path-Planning Algorithm for UAV-Based Contact Inspection

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 642
Author(s):  
Luis Miguel González de Santos ◽  
Ernesto Frías Nores ◽  
Joaquín Martínez Sánchez ◽  
Higinio González Jorge
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Execution Time ◽  
Point Cloud ◽  
Indoor Environments ◽  
Calculation Algorithm ◽  
Time Restrictions ◽  
Planning Algorithm ◽  
Inspection Tasks ◽  
Path Planning Algorithm

Nowadays, unmanned aerial vehicles (UAVs) are extensively used for multiple purposes, such as infrastructure inspections or surveillance. This paper presents a real-time path planning algorithm in indoor environments designed to perform contact inspection tasks using UAVs. The only input used by this algorithm is the point cloud of the building where the UAV is going to navigate. The algorithm is divided into two main parts. The first one is the pre-processing algorithm that processes the point cloud, segmenting it into rooms and discretizing each room. The second part is the path planning algorithm that has to be executed in real time. In this way, all the computational load is in the first step, which is pre-processed, making the path calculation algorithm faster. The method has been tested in different buildings, measuring the execution time for different paths calculations. As can be seen in the results section, the developed algorithm is able to calculate a new path in 8–9 milliseconds. The developed algorithm fulfils the execution time restrictions, and it has proven to be reliable for route calculation.

Development and analysis of DAYANI arc contour intelligent technique for navigation of two-wheeled mobile robot

2018 ◽  
Vol 45 (5) ◽  
pp. 688-702 ◽  
Author(s):  
Dayal R. Parhi ◽  
Animesh Chhotray
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Wheeled Mobile Robot ◽  
Weight Functions ◽  
Feasible Point ◽  
Content Type ◽  
Intelligent Technique ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Incremental Step

PurposeThis paper aims to generate an obstacle free real time optimal path in a cluttered environment for a two-wheeled mobile robot (TWMR).Design/methodology/approachThis TWMR resembles an inverted pendulum having an intermediate body mounted on a robotic mobile platform with two wheels driven by two DC motors separately. In this article, a novel motion planning strategy named as DAYANI arc contour intelligent technique has been proposed for navigation of the two-wheeled self-balancing robot in a global environment populated by obstacles. The developed new path planning algorithm evaluates the best next feasible point of motion considering five weight functions from an arc contour depending upon five separate navigational parameters.FindingsAuthenticity of the proposed navigational algorithm has been demonstrated by computing the path length and time taken through a series of simulations and experimental verifications and the average percentage of error is found to be about 6%.Practical implicationsThis robot dynamically stabilizes itself with taller configuration, can spin on the spot and rove along through obstacles with smaller footprints. This diversifies its areas of application to both indoor and outdoor environments especially with very narrow spaces, sharp turns and inclined surfaces where its multi-wheel counterparts feel difficult to perform.Originality/valueA new obstacle avoidance and path planning algorithm through incremental step advancement by evaluating the best next feasible point of motion has been established and verified through both experiment and simulation.

scholarly journals Path Planning for Highly Automated Driving on Embedded GPUs

2018 ◽  
Vol 8 (4) ◽  
pp. 35 ◽  
Author(s):  
Jörg Fickenscher ◽  
Sandra Schmidt ◽  
Frank Hannig ◽  
Mohamed Bouzouraa ◽  
Jürgen Teich
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Autonomous Driving ◽  
Automated Driving ◽  
Computing Power ◽  
Planning Algorithm ◽  
Time Requirements ◽  
Evaluation Platform ◽  
Path Planning Algorithm ◽  
Highly Automated Driving

The sector of autonomous driving gains more and more importance for the car makers. A key enabler of such systems is the planning of the path the vehicle should take, but it can be very computationally burdensome finding a good one. Here, new architectures in ECU are required, such as GPU, because standard processors struggle to provide enough computing power. In this work, we present a novel parallelization of a path planning algorithm. We show how many paths can be reasonably planned under real-time requirements and how they can be rated. As an evaluation platform, an Nvidia Jetson board equipped with a Tegra K1 SoC was used, whose GPU is also employed in the zFAS ECU of the AUDI AG.

scholarly journals 2D Lidar-Based SLAM and Path Planning for Indoor Rescue Using Mobile Robots

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xuexi Zhang ◽  
Jiajun Lai ◽  
Dongliang Xu ◽  
Huaijun Li ◽  
Minyue Fu
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Basic System ◽  
Rescue Robot ◽  
Planning Algorithm ◽  
Local Path ◽  
Slam Algorithm ◽  
Path Planning Algorithm

As the basic system of the rescue robot, the SLAM system largely determines whether the rescue robot can complete the rescue mission. Although the current 2D Lidar-based SLAM algorithm, including its application in indoor rescue environment, has achieved much success, the evaluation of SLAM algorithms combined with path planning for indoor rescue has rarely been studied. This paper studies mapping and path planning for mobile robots in an indoor rescue environment. Combined with path planning algorithm, this paper analyzes the applicability of three SLAM algorithms (GMapping algorithm, Hector-SLAM algorithm, and Cartographer algorithm) in indoor rescue environment. Real-time path planning is studied to test the mapping results. To balance path optimality and obstacle avoidance, A ∗ algorithm is used for global path planning, and DWA algorithm is adopted for local path planning. Experimental results validate the SLAM and path planning algorithms in simulated, emulated, and competition rescue environments, respectively. Finally, the results of this paper may facilitate researchers quickly and clearly selecting appropriate algorithms to build SLAM systems according to their own demands.

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