Smooth Path Planning for Unmanned Aerial Vehicles with Airspace Restrictions

Upadhyay, Saurabh; Ratnoo, Ashwini

doi:10.2514/1.g002400

Cited by 31 publications

(12 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Obstacle avoidance in an open territory is an even harder task. In [ 41 ], convex polygon flight paths, which should be used to avoid ground obstacles of various shapes, are generated. Alternatively, as in [ 42 ], a certain safety buffer zone around the ground obstacles is applied and Dubins paths are used to look for an optimal flight path.…”

Section: Dubins Paths Methodologymentioning

confidence: 99%

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

Kikutis

Stankūnas

Rudinskas

et al. 2017

Sensors

View full text Add to dashboard Cite

Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.

show abstract

Section: Dubins Paths Methodologymentioning

confidence: 99%

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

Kikutis

Stankūnas

Rudinskas

et al. 2017

Sensors

View full text Add to dashboard Cite

show abstract

“…where ( ) = ( ), ( ) . Differentiating (22) with respect to time and using the definition of given in (14), determines the following equation:…”

Section: A Collision Avoidance Controller For a Single Obstaclementioning

confidence: 99%

“…By differentiating (15) with respect to time and using the definition of provided in (14), the following equation is obtained:…”

Section: A Collision Avoidance Controller For a Single Obstaclementioning

confidence: 99%

See 1 more Smart Citation

Collision Avoidance for an Unmanned Aerial Vehicle in the Presence of Static and Moving Obstacles

Marchidan

Bakolas

2020

Journal of Guidance, Control, and Dynamics

View full text Add to dashboard Cite

This paper presents a new collision avoidance procedure for unmanned aerial vehicles in the presence of static and moving obstacles. The proposed procedure is based on a new form of local parametrized guidance vector fields, called collision avoidance vector fields, that produce smooth and intuitive maneuvers around obstacles. The maneuvers follow nominal collisionfree paths which we refer to as streamlines of the collision avoidance vector fields. In the case of multiple obstacles, the proposed procedure determines a mixed vector field that blends the collision avoidance vector field of each obstacle and assumes its form whenever a pre-defined distance threshold is reached. Then, in accordance to the computed guidance vector fields, different collision avoidance controllers that generate collision-free maneuvers are developed. Furthermore, it is shown that any tracking controller with convergence guarantees can be used with the avoidance controllers to track the streamlines of the collision avoidance vector fields. Finally, numerical simulations demonstrate the efficacy of the proposed approach and its ability to avoid collisions with static and moving pop-up threats in three different practical scenarios.

show abstract

“…Whether it is a graph-based search method or a local navigation algorithm, they mostly aim at a flat environment. For path planning in a space environment, popular approaches are mainly to integrate obstacles, speeds, and path lengths into constraints and generate trajectories by curve parameterization [25,26]. Most of the numerical methods use path point parameterization to define splines, polynomials, and so on.…”

Section: Introductionmentioning

confidence: 99%

Obstacle Avoidance in a Three-Dimensional Dynamic Environment Based on Fuzzy Dynamic Windows

Xia

2021

Applied Sciences

View full text Add to dashboard Cite

This paper presents a real-time path planning approach for controlling the motion of space-based robots. The algorithm can plan three-dimensional trajectories for agents in a complex environment which includes numerous static and dynamic obstacles, path constraints, and/or performance constraints. This approach is extended based on the dynamic window approach (DWA). As the classic reactive method for obstacle avoidance, DWA uses an optimized function to select the best motion command. The original DWA optimization function consists of three weight terms. Changing the weights of these terms will change the behavior of the algorithm. In this paper, to improve the evaluation ability of the optimization function and the robot’s ability to adapt to the environment, a new optimization function is designed and combined with fuzzy logic to adjust the weights of each parameter of the optimization function. Given that DWA has the defect of local minima, which makes the robot hard to escape U-shaped obstacles, a dual dynamic window method and local goals are adopted in this article to help the robot escape local minima. By comparison, the proposed method is superior to traditional DWA and fuzzy DWA (F_DWA) in terms of computational efficiency, smoothness and security.

show abstract

Smooth Path Planning for Unmanned Aerial Vehicles with Airspace Restrictions

Cited by 31 publications

References 23 publications

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

Collision Avoidance for an Unmanned Aerial Vehicle in the Presence of Static and Moving Obstacles

Obstacle Avoidance in a Three-Dimensional Dynamic Environment Based on Fuzzy Dynamic Windows

Contact Info

Product

Resources

About