Collision-free trajectory planning based on Maneuver Selection-Particle Swarm Optimization

Alejo, David; Cobano, J. A.; Heredia, Guillermo; Ollero, A.

doi:10.1109/icuas.2015.7152277

Cited by 15 publications

(6 citation statements)

References 24 publications

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“…Different drones in a swarm can have different sets of sensors, depending on the task. At the same time, all drones should be able to avoid collisions in real time based on the sensory data [12,13]. Indeed, a dense swarm of drones emphasises the need for having an efficient embedded collision avoidance technique/methodology so that the UAVs can individually detect and avoid each other and other objects/obstacles in their neighbourhood [14].…”

Section: Motivationmentioning

confidence: 99%

Low-cost ultrasonic based object detection and collision avoidance method for autonomous robots

Mohamed

Haghbayan

Heikkonen

et al. 2020

Int. j. inf. tecnol.

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This work focuses on the development of an effective collision avoidance algorithm that detects and avoids obstacles autonomously in the vicinity of a potential collision by using a single ultrasonic sensor and controlling the movement of the vehicle. The objectives are to minimise the deviation from the vehicle’s original path and also the development of an algorithm utilising one of the cheapest sensors available for very lost cost systems. For instance, in a scenario where the main ranging sensor malfunctions, a backup low cost sensor is required for safe navigation of the vehicle while keeping the deviation to a minimum. The developed algorithm utilises only one ultrasonic sensor and approximates the front shape of the detected object by sweeping the sensor mounted on top of the unmanned vehicle. In this proposed approach, the sensor is rotated for shape approximation and edge detection instead of moving the robot around the encountered obstacle. It has been tested in various indoor situations using different shapes of objects, stationary objects, moving objects, and soft or irregularly shaped objects. The results show that the algorithm provides satisfactory outcomes by entirely avoiding obstacles and rerouting the vehicle with a minimal deviation.

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Section: Motivationmentioning

confidence: 99%

Low-cost ultrasonic based object detection and collision avoidance method for autonomous robots

Mohamed

Haghbayan

Heikkonen

et al. 2020

Int. j. inf. tecnol.

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“…Moreover, the algorithm is easy to implement and has low computational overhead. The usage of PSO in the UAS path planning is described for example in Sujit and Beard, 89 Alejo et al, 90 and Phung et al 91 Mixed-integer linear programming. The problem of vehicle path planning can also be formulated as a linear program.…”

Section: Optimized Trajectory Approachmentioning

confidence: 99%

Sense and avoid for small unmanned aircraft systems: Research on methods and best practices

Skowron

Chmielowiec

Glowacka

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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In this study, we discuss recent advances and state-of-the-art sense-and-avoid solutions for small unmanned aircraft systems. The purpose of this paper is to equip the reader with the most up-to-date information on research and commercial efforts aimed at introducing autonomous small unmanned aircraft systems into the shared airspace. We present a broad overview of the regulatory environment, current abilities, and limitations of various sensor types as well as algorithmic and computational aspects of establishing a reliable sense-and-avoid platform. This paper reviews a substantial portion of the literature, focusing on developing reliable sense-and-avoid systems. It brings together information from various sources, including commercial drone and sensor manufacturers, regulatory agencies, as well as basic research performed in this regard. While academic and industrial research activities aimed at developing an effective sense-and-avoid system for small unmanned aircraft systems are intensifying, the current technology does not yet allow for a comprehensive solution that would enable autonomous flight. However, recent advances in hardware miniaturization, increases in computational power, and new algorithmic solutions allow us to remain optimistic about future developments.

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“…This method provides a simple and computationally useful algorithm for optimizing a wide range of functions. The use of PSOs as part of a UAS path-planning algorithm has been employed successfully by numerous researchers [30,35,[41][42][43][44]. Roberge et al [45] provided a comparison of GAs and PSOs for UAS path planning.…”

Section: Fixed Targetmentioning

confidence: 99%

Multiple-Scenario Unmanned Aerial System Control: A Systems Engineering Approach and Review of Existing Control Methods

2016

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Abstract:The use of unmanned aerial systems (UASs) in both the public and military environments is predicted to grow significantly. As the demand for UASs grows, the availability of more robust and capable vehicles that can perform multiple mission types will be needed. In the public sector, the demand will grow for UASs to be used for agriculture, forestry, and search and rescue missions. Militaries continue to demand more UAS capabilities for diverse operations around the world. Significant research has been performed and continues to progress in the areas of autonomous UAS control. A majority of the work focuses on subsets of UAS control: path planning, autonomy, small UAS controls, and sensors. Minimal work exists on a system-level problem of multiple-scenario UAS control for integrated systems. This paper provides a high-level modular system architecture definition that is modifiable across platform types and mission requirements. A review of the current research and employment of UAS capabilities is provided to evaluate the state of the capabilities required to enable the proposed architecture.

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Collision-free trajectory planning based on Maneuver Selection-Particle Swarm Optimization

Cited by 15 publications

References 24 publications

Low-cost ultrasonic based object detection and collision avoidance method for autonomous robots

Low-cost ultrasonic based object detection and collision avoidance method for autonomous robots

Sense and avoid for small unmanned aircraft systems: Research on methods and best practices

Multiple-Scenario Unmanned Aerial System Control: A Systems Engineering Approach and Review of Existing Control Methods

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