RRT* GL Based Optimal Path Planning for Real-Time Navigation of UAVs

Aguilar, Wilbert G.; Morales, Stephanie; Ruiz, Hugo; Abad, Vanessa

doi:10.1007/978-3-319-59147-6_50

Cited by 36 publications

(11 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a future work, we extrapolate video freeze detection to onboard applications as people detection [28] [29], navigation [30] [31] [32], obstacle avoidance [33] [34] [35], and mapping [36].…”

Section: Discussionmentioning

confidence: 99%

Motion intention optimization for multirotor robust video stabilization

Aguilar

Ángulo

Pardo

2017

2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

Self Cite

View full text Add to dashboard Cite

Abstract-In this paper we present an optimization algorithm for simultaneously detecting video freeze and obtaining the minimum number of the frame required in motion intention estimation for real time robust video stabilization on multirotor unmanned aerial vehicles. A combination of a filter and a threshold is used to the video freeze detection, and for optimizing the algorithm, we find the minimum number of frames for motion intention estimation without decrease the performance.

show abstract

Section: Discussionmentioning

confidence: 99%

Motion intention optimization for multirotor robust video stabilization

Aguilar

Ángulo

Pardo

2017

2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, a detailed study of SLAM is out of the scope of this survey. Aguilar developed a path planner based on RRT* [197] for real-time navigation.…”

Section: Hybrid Mappingmentioning

confidence: 99%

Survey of Datafusion Techniques for Laser and Vision Based Sensor Integration for Autonomous Navigation

Kolar

Benavidez

Jamshidi

2020

Sensors

View full text Add to dashboard Cite

This paper focuses on data fusion, which is fundamental to one of the most important modules in any autonomous system: perception. Over the past decade, there has been a surge in the usage of smart/autonomous mobility systems. Such systems can be used in various areas of life like safe mobility for the disabled, senior citizens, and so on and are dependent on accurate sensor information in order to function optimally. This information may be from a single sensor or a suite of sensors with the same or different modalities. We review various types of sensors, their data, and the need for fusion of the data with each other to output the best data for the task at hand, which in this case is autonomous navigation. In order to obtain such accurate data, we need to have optimal technology to read the sensor data, process the data, eliminate or at least reduce the noise and then use the data for the required tasks. We present a survey of the current data processing techniques that implement data fusion using different sensors like LiDAR that use light scan technology, stereo/depth cameras, Red Green Blue monocular (RGB) and Time-of-flight (TOF) cameras that use optical technology and review the efficiency of using fused data from multiple sensors rather than a single sensor in autonomous navigation tasks like mapping, obstacle detection, and avoidance or localization. This survey will provide sensor information to researchers who intend to accomplish the task of motion control of a robot and detail the use of LiDAR and cameras to accomplish robot navigation.

show abstract

“…In particular, we interest in the problem of multi-UAV path planning operating in a dynamic environment, where a team of low-cost UAV is designed to perform complex missions while visiting the desired locations. As the number of UAV increases in the team, path planning algorithms such as A* [19] [20], Dijkstra [21], [22] or RRT [23], [13], may require high-performance capabilities (memory and processing time) to find a valid solution. Our proposed algorithm is a good choice for solving this problem's type since this method is not coupled with its high dimensionality.…”

Section: Future Workmentioning

confidence: 99%

UAV Path Planning for Civil Applications

Asmaa¹,

Boukhdir²,

Hicham³

2019

IJACSA

View full text Add to dashboard Cite

We will present a simple and efficient algorithm for solving the path planning problem for civil UAV operating in a dynamic or incomplete environment. This algorithm searches for a continuous waypoints sequence starting from the initial configuration, visiting all the desired locations and reaching the final position. We will present our proposed algorithm on two steps: The first produces a sorted location set. The second step generates an optimal path for the overall mission. The same algorithm constructs the initial path or re-plans a new one when changes occur to the configuration space. To prove the effectiveness of our proposed algorithm, we will provide computer simulations. A comparison of many results will show that this algorithm yields good experience performance over a wide variety of examples.

show abstract

RRT* GL Based Optimal Path Planning for Real-Time Navigation of UAVs

Cited by 36 publications

References 29 publications

Motion intention optimization for multirotor robust video stabilization

Motion intention optimization for multirotor robust video stabilization

Survey of Datafusion Techniques for Laser and Vision Based Sensor Integration for Autonomous Navigation

UAV Path Planning for Civil Applications

Contact Info

Product

Resources

About