Control of multiple non-holonomic air vehicles under wind uncertainty using Model Predictive Control and decentralized navigation functions

Roussos, Giannis; Chaloulos, Georgios; Kyriakopoulos, Kostas J.; Lygeros, John

doi:10.1109/cdc.2008.4738792

Cited by 22 publications

(21 citation statements)

References 16 publications

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“…65 Navigation function methods have also been combined with MPC; this supplies some type of planning into the future to reject disturbances. 227 Navigation function methods have also been applied to threedimensional scenarios. 226 In cases where finite acceleration bounds are present (but still without any nonholonomic constraints), a mutual repulsion-based navigation system with a more sophisticated avoidance function has been proven to avoid collisions for up to three vehicles.…”

Section: Potential Field Methodsmentioning

confidence: 99%

Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey

2014

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SUMMARYWe review a range of techniques related to navigation of unmanned vehicles through unknown environments with obstacles, especially those that rigorously ensure collision avoidance (given certain assumptions about the system). This topic continues to be an active area of research, and we highlight some directions in which available approaches may be improved. The paper discusses models of the sensors and vehicle kinematics, assumptions about the environment, and performance criteria. Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are all reviewed. In preference to global approaches based on full knowledge of the environment, particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.

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Section: Potential Field Methodsmentioning

confidence: 99%

Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey

2014

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“…This will allow a natural extension of operational scenarios in which the UAV will be able to participate successfully, especially in mixed-initiative areas [13,14].…”

Section: Sense and Avoidmentioning

confidence: 98%

Unmanned aircraft systems in maritime operations: Challenges addressed in the scope of the SEAGULL project

Marques

Dias

Santos

et al. 2015

OCEANS 2015 - Genova

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The SEAGULL project aims at the development of intelligent systems to support maritime situation awareness based on unmanned aerial vehicles. It proposes to create an intelligent maritime surveillance system by equipping unmanned aerial vehicles (UAVs) with different types of optical sensors. Optical sensors such as cameras (visible, infrared, multi and hyper spectral) can contribute significantly to the generation of situational awareness of maritime events such as (i) detection and georeferencing of oil spills or hazardous and noxious substances; (ii) tracking systems (e.g. vessels, shipwrecked, lifeboat, debris, etc.); (iii) recognizing behavioral patterns (e.g. vessels rendezvous, high-speed vessels, atypical patterns of navigation, etc.); and (iv) monitoring parameters and indicators of good environmental status. On-board transponders will be used for collision detection and avoidance mechanism (sense and avoid). This paper describes the core of the research and development work done during the first 2 years of the project with particular emphasis on the following topics: system architecture, automatic detection of sea vessels by vision sensors and custom designed computer vision algorithms; and a sense and avoid system developed in the theoretical framework of zero-sum differential games.

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“…It is an improved potential field method with no local minima, that guarantees path convergence to the destination in a world with stationary obstacles. Specifically, we use Dipolar Navigation functions [15] which allow the use of a desired orientation at the goal point. Moreover, this method is adapted to work in an environment with partially known objects.…”

Section: B Path Planning Using Navigation Functionsmentioning

confidence: 99%

Obstacle avoidance using echo sounder sonar

Calado¹,

Gomes²,

Nogueira³

et al. 2011

OCEANS 2011 IEEE - Spain

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Developing obstacle avoidance algorithms for low cost Autonomous Underwater Vehicles using single beam returned echo sounder sonar is a difficult task. In this paper, we propose an intelligent obstacle avoidance algorithm that maps the obstacle, avoids it with a guarantee that it will not get stuck and efficiently traverses a path towards the destination using navigation functions. We present a complete obstacle avoidance system with the help of hybrid automata, probabilistic mapping and navigation functions. Simulation results are presented showing the validity of our approach.

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Control of multiple non-holonomic air vehicles under wind uncertainty using Model Predictive Control and decentralized navigation functions

Cited by 22 publications

References 16 publications

Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey

Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey

Unmanned aircraft systems in maritime operations: Challenges addressed in the scope of the SEAGULL project

Obstacle avoidance using echo sounder sonar

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