Bi-level Flight Path Planning of UAV Formations with Collision Avoidance

To plan the path for UAV flying in the complex, dense and irregular obstacles environment, this paper proposed an obstacle collision-avoidance detection model and designed an UAV path planning algorithm based on irregular obstacles collision-avoidance detection (IOCAD), which includes irregular obstacles pretreatment method. The proposed method uses the grid method to model the environment. Rough set theory and convexity filling are used to pretreat the obstacles, and the ray method is used to select the available points. The intersection detection and the distance detection are held for the obstacle to the flight path. The objective function minimizes the distance from the obstacle to the flight path to get planned paths. The simulation results show that the proposed method can effectively plan the paths with the constraints of the assumed environment and UAV performances. It is shown that the performance of the proposed method is sensitive to the grid length and safety distance. The optimized values for the grid length and safety distance are 0.5 km and 0.4 km respectively.

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Integrated Path Planning and Tracking Control of Autonomous Vehicle for Collision Avoidance based on Model Predictive Control and Potential Field

2020 20th International Conference on Control, Automation and Systems (ICCAS) ◽

10.23919/iccas50221.2020.9268369 ◽

2020 ◽

Author(s):

Chanho. Ko ◽

Seungho. Han ◽

Minseong. Choi ◽

Kyung-Soo. Kim

Keyword(s):

Path Planning ◽

Model Predictive Control ◽

Collision Avoidance ◽

Predictive Control ◽

Potential Field ◽

Tracking Control ◽

Autonomous Vehicle

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COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

Journal of Marine Science and Engineering ◽

10.3390/jmse9040405 ◽

2021 ◽

Vol 9 (4) ◽

pp. 405

Author(s):

Raphael Zaccone

Keyword(s):

Path Planning ◽

Real Time ◽

Collision Avoidance ◽

Autonomous Navigation ◽

Optimal Path ◽

Open Water ◽

Optimal Path Planning ◽

Guidance And Control ◽

Real Time Applications ◽

And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

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Collision avoidance for a redundant manipulator in an unstructured environment with a simplified path planning and multiple self-organizing maps

2005 IEEE International Conference on Robotics and Biomimetics - ROBIO ◽

10.1109/robio.2005.246286 ◽

2005 ◽

Author(s):

Min Han ◽

N. Okada ◽

E. Kondo

Keyword(s):

Path Planning ◽

Collision Avoidance ◽

Redundant Manipulator ◽

Self Organizing Maps ◽

Unstructured Environment ◽

Self Organizing

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A Novel Approach for Two-Stage UAV Path Planning in Pipeline Network Inspection

Volume 3: Operations, Monitoring, and Maintenance; Materials and Joining ◽

10.1115/ipc2020-9604 ◽

2020 ◽

Author(s):

Rui Qiu ◽

Yongtu Liang

Keyword(s):

Path Planning ◽

Large Scale ◽

Flight Path ◽

Mixed Integer ◽

Optimization Approach ◽

Two Stage ◽

Calculation Time ◽

Pipeline Network ◽

Second Stage ◽

Computational Performance

Abstract Currently, unmanned aerial vehicle (UAV) provides the possibility of comprehensive coverage and multi-dimensional visualization of pipeline monitoring. Encouraged by industry policy, research on UAV path planning in pipeline network inspection has emerged. The difficulties of this issue lie in strict operational requirements, variable flight missions, as well as unified optimization for UAV deployment and real-time path planning. Meanwhile, the intricate structure and large scale of the pipeline network further complicate this issue. At present, there is still room to improve the practicality and applicability of the mathematical model and solution strategy. Aiming at this problem, this paper proposes a novel two-stage optimization approach for UAV path planning in pipeline network inspection. The first stage is conventional pre-flight planning, where the requirement for optimality is higher than calculation time. Therefore, a mixed integer linear programming (MILP) model is established and solved by the commercial solver to obtain the optimal UAV number, take-off location and detailed flight path. The second stage is re-planning during the flight, taking into account frequent pipeline accidents (e.g. leaks and cracks). In this stage, the flight path must be timely rescheduled to identify specific hazardous locations. Thus, the requirement for calculation time is higher than optimality and the genetic algorithm is used for solution to satisfy the timeliness of decision-making. Finally, the proposed method is applied to the UAV inspection of a branched oil and gas transmission pipeline network with 36 nodes and the results are analyzed in detail in terms of computational performance. In the first stage, compared to manpower inspection, the total cost and time of UAV inspection is decreased by 54% and 56% respectively. In the second stage, it takes less than 1 minute to obtain a suboptimal solution, verifying the applicability and superiority of the method.

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Path Planning Scheme for Collision Avoidance in Unmanned Aerial Vehicle Traffic Management System

10.1109/conecct52877.2021.9622656 ◽

2021 ◽

Author(s):

Amaanullah ◽

Muhammed Ahmed Lamba ◽

Surya Prakash S ◽

Shrikant S. Tangade ◽

Syed Sehraab Nawaz ◽

...

Keyword(s):

Path Planning ◽

Collision Avoidance ◽

Unmanned Aerial Vehicle ◽

Traffic Management ◽

Management System ◽

Vehicle Traffic ◽

Planning Scheme ◽

Aerial Vehicle ◽

Traffic Management System

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3D FLIGHT PATH PLANNING FOR MULTIROTOR UAV

Review of the Air Force Academy ◽

10.19062/1842-9238.2020.18.1.1 ◽

2020 ◽

Vol 18 (1) ◽

pp. 5-16

Author(s):

Róbert SZABOLCSI ◽

Keyword(s):

Path Planning ◽

Flight Path

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Obstacle Avoidace Robot Using LabView

IAES International Journal of Robotics and Automation (IJRA) ◽

10.11591/ijra.v4i3.pp164-167 ◽

2015 ◽

Vol 4 (3) ◽

pp. 164

Author(s):

Tasher Ali Sheikh ◽

Swacheta Dutta ◽

Smriti Baruah ◽

Pooja Sharma ◽

Sahadev Roy

Keyword(s):

Path Planning ◽

Real Time ◽

Collision Avoidance ◽

Obstacle Avoidance ◽

Autonomous Robotics ◽

Continuous Transition ◽

Heavy Burden ◽

Avoidance Strategy ◽

Small Period ◽

Specific Amount

The concept of path planning and collision avoidance are two of the most common theories applied for designing and developing in advanced autonomous robotics applications. NI LabView makes it possible to implement real-time processor for obstacle avoidance. The obstacle avoidance strategy ensures that the robot whenever senses the obstacle stops without being collided and moves freely when path is free, but sometimes there exists a probability that once the path is found free and the robot starts moving, then within a fraction of milliseconds, the robot again sense the obstacle and it stops. This continuous swing of stop and run within a very small period of time may cause heavy burden on the system leading to malfunctioning of the components of the system. This paper deals with overcoming this drawback in a way that even after the robot calculates the path is free then also it will wait for a specific amount of time before running it. So as to confirm that if again the sensor detects the obstacle within that specified period then robot don’t need to transit its state suddenly thus avoiding continuous transition of run and stop. Thus it reduces the heavy burden on the system.

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