Modeling and Control Design of a Robotic Sailboat

on this list. I would never have been able to complete this thesis without your dedication, inspiration and wisdom. I wish you all the best and thank you from the bottom of my heart! I would first like to thank the supervisory committee, for their guidance, support, endless patience and direction through the winding path that finally led to this work. Brian, I want to thank you for your patient support and for all of the opportunities I was given to further my research. Bruce, you provided me with the vision that I needed to choose the right direction to successfully complete my dissertation. Eric, your insightful feedback pushed me to sharpen my thinking and brought my work to a higher level. I would like to acknowledge my colleagues from the Computer Science Department at the University of Victoria. In particular, Lucky and Robert Steacy, your feedback and assistance helped me time and time again. Thank you to Jerome and Tyler from the Coast Capital Innovation Centre for your support and guidance. In addition, I would like to thank my parents for their for endless love, support, patience and faith in me. You are always there for me. Finally, I could not have completed this dissertation without the support of my friends who provided stimulating discussions as well as happy distractions to rest my mind outside of my research.

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“…Unfortunately, it usually leads the captain to shift his attention from other, sometimes vital activities. [64]…”

Section: S2 Data Sourcesmentioning

confidence: 99%

Obstacle Detection for Image-Guided Surface Water Navigation

Sadhu

Albu

Hoeberechts

et al. 2016

2016 13th Conference on Computer and Robot Vision (CRV)

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“…It assumes an optimal sail configuration. The polar diagram of the sailboat used in this study and depicted on figure 2 has been obtained by numerical simulations, in steady state conditions [12]. The direction to follow γ r is equal to the angle θ seg i of the segment seg i w.r.t.…”

Section: A Global Path Planning Using Prm-dijkstramentioning

confidence: 99%

“…A simplified 3-DOF model of the sailboat presented in [12] is used for control design purposes. This assumes that:…”

Section: A 3-dof Dynamic Modelmentioning

confidence: 99%

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Routing and course control of an autonomous sailboat

Saoud

Hua

Plumet

et al. 2015

2015 European Conference on Mobile Robots (ECMR)

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In this paper, we present a layered control scheme for an autonomous sailboat. The high level control uses an adjusted PRM-Dijkstra algorithm for the routing (global path planning) of autonomous sailboat. This algorithm exploits the sailboat kinematics and wind distribution on the map. For the low level control, we design a new nonlinear course (direction of the velocity vector) controller that exhibits superior performance compared to conventionally used heading controller. A smoothing function is also introduced in the design of the controller to switch easily from course control to heading control, especially when course measurements are noisy at low speed.

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“…Thus, while the position and the speed of AUVs and surface vehicles can be controlled by motors, the limitation on the speed of sailboats and the wind conditions must be taken into account. Many low-level and high-level control systems designed for sailboats can be found in the literature [1][2][3][4][5][6][7] to follow line, to avoid obstacles, to trace a path, or to reach a target point. This paper focuses on the problem of a fleet of sailboats to collect data from moving targets (buoys, fish, boats), as an application of the Dynamic Travelling Salesman Problem (DTSP).…”

Section: Introductionmentioning

confidence: 99%

Genetic algorithm‐based multiple moving target reaching using a fleet of sailboats

Viel

Ulysse

Wan

et al. 2019

IET cyber-systems robotics

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This paper addresses the problem of Dynamic Traveling Salesman Problem (DTSP) for a multi-agent system using a fleet of sailboats. A genetic algorithm (GA) is proposed which attributes to each agent a varying number of targets to be collected. GA allows to obtain a suboptimal solution in the shortest time possible. Moreover, this paper adapts it to the specific problem involving a fleet of sailboats, which is a challenging task with comparison to Unmanned Surface Vehicle (USV) or motorized vehicles in terms of the propulsion. Therein motors can be flexibly controlled while sailboat movements are constrained by available wind direction and speed. Thus the method takes into account wind conditions at various locations of the sailboat. Simulation results demonstrate the effectiveness of the proposed approach.

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Modeling and Control Design of a Robotic Sailboat

Cited by 8 publications

References 11 publications

Obstacle Detection for Image-Guided Surface Water Navigation

Obstacle Detection for Image-Guided Surface Water Navigation

Routing and course control of an autonomous sailboat

Genetic algorithm‐based multiple moving target reaching using a fleet of sailboats

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