Obstacle Avoidance-Based Autonomous Navigation of a Quadrotor System

Alanezi, Mohammed Ateeq; Haruna, Zaharuddeen; Sha’aban, Yusuf A.; Bouchekara, Houssem R. E. H.; Nahas, Mouaaz; Shahriar, Mohammad Shoaib

doi:10.3390/drones6100288

Cited by 15 publications

(6 citation statements)

References 33 publications

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“…[126] developed trajectory control algorithms using a PID controller that should control the required linear coordinates of the quadrotor UAV over the entire course. [127] modeled and simulated the autonomous navigation of a quadrotor system based on obstacle avoidance in Simulink. Two genetic algorithm-based PID controllers were developed for quadrotor altitude and attitude control using integral squared error (ISE) and integral time absolute error (ITAE).…”

Section: A Research On Pid Controlmentioning

confidence: 99%

A Survey of Indoor UAV Obstacle Avoidance Research

Xiong

Yan

et al. 2023

IEEE Access

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UAV obstacle avoidance technology is one of the key factors to realize UAV autonomous flight, efficient and accurate obstacle avoidance is significant to complete the UAV autonomous flight task. In contrast, the dynamic, real-time and uncertainty of the environment in which the UAV is located makes the problem very tricky, especially in the indoor environment. At present, a large number of scholars have shown strong interest in the indoor UAV obstacle avoidance problem. With the rapid development of computer technology and hardware devices, many intelligent algorithms have been proposed to solve the obstacle avoidance problem. However, the research on indoor UAV obstacle avoidance technology is not comprehensive enough, and there is a lack of summarization of the research results in recent years. This paper introduces the sensor modules commonly used for indoor UAV environment sensing, related obstacle avoidance methods based on sensory detection. Classifies and composes the commonly used UAV path planning obstacle avoidance algorithms, and gives several representative UAV flight control research methods. This paper summarizes the advantages and disadvantages of different perception modules and detection methods applied to UAV obstacle avoidance tasks, and compares various current path planning methods. Finally, the critical difficulties and challenges faced in the field of indoor UAV obstacle avoidance are discussed, and future research in the field of UAV obstacle avoidance has prospected.

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Section: A Research On Pid Controlmentioning

confidence: 99%

A Survey of Indoor UAV Obstacle Avoidance Research

Xiong

Yan

et al. 2023

IEEE Access

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“…Unmanned aerial vehicles (UAVs) [1][2][3][4][5][6][7] are used in many fields, such as intelligent confrontation [8], target rounding [9] and intelligent transportation [10], because of their characteristics of being unmanned, having good concealment and having no casualties. UAV pursuit-evasion [11] involves a game between two UAVs with competing interests.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Maneuver Decision Method Based on PG-Option for UAV Pursuit-Evasion Game

Zhang

et al. 2023

Drones

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Aiming at the autonomous decision-making problem in an Unmanned aerial vehicle (UAV) pursuit-evasion game, this paper proposes a hierarchical maneuver decision method based on the PG-option. Firstly, considering various situations of the relationship of both sides comprehensively, this paper designs four maneuver decision options: advantage game, quick escape, situation change and quick pursuit, and the four options are trained by Soft Actor-Critic (SAC) to obtain the corresponding meta-policy. In addition, to avoid high dimensions in the state space in the hierarchical model, this paper combines the policy gradient (PG) algorithm with the traditional hierarchical reinforcement learning algorithm based on the option. The PG algorithm is used to train the policy selector as the top-level strategy. Finally, to solve the problem of frequent switching of meta-policies, this paper sets the delay selection of the policy selector and introduces the expert experience to design the termination function of the meta-policies, which improves the flexibility of switching policies. Simulation experiments show that the PG-option algorithm has a good effect on UAV pursuit-evasion game and adapts to various environments by switching corresponding meta-policies according to current situation.

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“…Ground mobile robots utilize mobile platforms like wheels, tracks, legs, or even biomimicry inspired by animals such as snakes. Aerial mobile robots include drones and helicopters, used for tasks like remote sensing, surveillance, and packet delivery [4,5]. Water surface mobile robots operate on water for data acquisition, environmental monitoring, and surveillance.…”

Section: Introductionmentioning

confidence: 99%

Path Planning Algorithms for Mobile Robots: A Survey

Haruna,

Bashir Mu’azu,

Umar

et al. 2023

Motion Planning for Dynamic Agents

Self Cite

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Mobile robots have applications in military (for reconnaissance, search and rescue operations, bomb detection, surveillance), transportation (for cargo and packet delivery), data acquisition, etc. For the mobile robots to be able to execute these tasks with minimum or no human intervention, they need to be autonomous and intelligent. Path planning (PP) is one of the most critical areas of concern in the field of autonomous mobile robots. It is about obtaining a collision-free motion optimal path based on either time, distance, energy or cost in a static or dynamic environment containing obstacles. However, power limitation hinders the mobile robots to accomplish their task of reaching the target location as there are several paths they can follow. Each of these paths has its own path length, cost (i.e., time to reach destination), and energy constraint, thus, the need to plan for an optimal path according to a certain performance criterion. Significant research has been conducted in recent years to address the PP problem. Hence, this chapter is aimed at presenting the different approaches for PP of mobile robots with respect to different optimality criteria (time, distance, energy and cost), challenges and making recommendations on possible areas of future research.

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Obstacle Avoidance-Based Autonomous Navigation of a Quadrotor System

Cited by 15 publications

References 33 publications

A Survey of Indoor UAV Obstacle Avoidance Research

A Survey of Indoor UAV Obstacle Avoidance Research

Hierarchical Maneuver Decision Method Based on PG-Option for UAV Pursuit-Evasion Game

Path Planning Algorithms for Mobile Robots: A Survey

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