A gain-scheduling control strategy and short-term path optimization with genetic algorithm for autonomous navigation of a sailboat robot

Santos, Davi Henrique dos; Gonçalves, Luiz Marcos Garcia

doi:10.1177/1729881418821830

Cited by 19 publications

(6 citation statements)

References 24 publications

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“…Finally, besides having the two twin sailboats constructed, we also consider using another simulation environment that we have built based on the N-Boat specifications (last item of Table 1 ) ( Dos Santos and Goncalves, 2019 ; Paravisi et al, 2019 ). By using simulators it is possible to customize the same variables for different vehicles, as often as necessary.…”

Section: Similar Projects (State Of the Art)mentioning

confidence: 99%

Sustainable Solutions for Sea Monitoring With Robotic Sailboats: N-Boat and F-Boat Twins

et al. 2022

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Strategic management and production of internal energy in autonomous robots is becoming a research topic with growing importance, especially for platforms that target long-endurance missions, with long-range and duration. It is fundamental for autonomous vehicles to have energy self-generation capability to improve energy autonomy, especially in situations where refueling is not viable, such as an autonomous sailboat in ocean traversing. Hence, the development of energy estimation and management solutions is an important research topic to better optimize the use of available energy supply and generation potential. In this work, we revisit the challenges behind the project design and construction for two fully autonomous sailboats and propose a methodology based on the Restricted Boltzmann Machine (RBM) in order to find the best way to manage the supplementary energy generated by solar panels. To verify the approach, we introduce a case study with our two developed sailboats that have planned payload with electric and electronics, and one of them is equipped with an electrical engine that may eventually help with the sailboat propulsion. Our current results show that it is possible to augment the system confidence level for the potential energy that can be harvested from the environment and the remaining energy stored, optimizing the energy usage of autonomous vehicles and improving their energy robustness.

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Section: Similar Projects (State Of the Art)mentioning

confidence: 99%

Sustainable Solutions for Sea Monitoring With Robotic Sailboats: N-Boat and F-Boat Twins

et al. 2022

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“…But the approach presented in this paper occupies both object detection along with autonomous navigation hand to hand. There are some examples of such systems [8,9] where the robot is able to acquire and facilitate autonomous movement. Different to our methods, the works presented here [10], is a method of simultaneous localization and mapping (SLAM) to integrate both object detection and autonomous floor mapping.…”

Section: Related Workmentioning

confidence: 99%

Alpha-N: Shortest Path Finder Automated Delivery Robot with Obstacle Detection and Avoiding System

Neloy¹,

Bindu²,

Alam³

et al. 2020

Intelligent Information and Database Systems

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Alpha-N -A self-powered, wheel-driven Automated Delivery Robot (ADR) is presented in this paper. The ADR is capable of navigating autonomously by detecting and avoiding objects or obstacles in its path. It uses a vector map of the path and calculates the shortest path by Grid Count Method (GCM) of Dijkstra's Algorithm. Landmark determination with Radio Frequency Identification (RFID) tags are placed in the path for identification and verification of source and destination, and also for the re-calibration of the current position. On the other hand, an Object Detection Module (ODM) is built by Faster R-CNN with VGGNet-16 architecture for supporting path planning by detecting and recognizing obstacles. The Path Planning System (PPS) is combined with the output of the GCM, the RFID Reading System (RRS) and also by the binary results of ODM. This PPS requires a minimum speed of 200 RPM and 75 seconds duration for the robot to successfully relocate its position by reading an RFID tag. In the result analysis phase, the ODM exhibits an accuracy of 83.75%, RRS shows 92.3% accuracy and the PPS maintains an accuracy of 85.3%. Stacking all these 3 modules, the ADR is built, tested and validated which shows significant improvement in terms of performance and usability comparing with other service robots.

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“…In most of these studies, robots carry vision systems to gather information about the environment. Considering the state of the art, Santos et al 18 propose an optimization method based on a genetic algorithm for the development of a navigation system for autonomous robotic sailing. Honarpardaz et al 19 suggest a generic experimental method to verify existing finger design approaches.…”

Section: Related Workmentioning

confidence: 99%

Intelligent Selective Compliance Articulated Robot Arm robot with object recognition in a multi-agent manufacturing system

Zakhama

Charrabi

Jelassi

2019

International Journal of Advanced Robotic Systems

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Nowadays, industry tends to adopt the smart factory concept in their production. Technology intelligence is applied to use all the resources efficiently. Robots and vision system are masters in this kind of industry. However, information transfer between the robot controller and the vision system poses a great challenge. Data exchange between these two systems shall be secure, and the transfer must be with a very high level of accuracy. In this article, a multi-platform software application using a vision system is performed to control a Selective Compliance Articulated Robot Arm robot. The software solution includes the detection of defaults in a product by calculating a compliance rate using an efficient algorithm. An analysis of four different algorithms related to histogram-based similarity functions is set. Then, the most efficient algorithm is integrated into the application that provides a secure communication between three different operating systems. Experiments in a multi-agent manufacturing center validate the effectiveness of the proposed method. Tests demonstrate the efficiency of the data transfer between the vision system and the multi-platform software application and the Selective Compliance Articulated Robot Arm robot. This data transfer can be controlled in a high accuracy manner without any additional manual parameters tuning.

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A gain-scheduling control strategy and short-term path optimization with genetic algorithm for autonomous navigation of a sailboat robot

Cited by 19 publications

References 24 publications

Sustainable Solutions for Sea Monitoring With Robotic Sailboats: N-Boat and F-Boat Twins

Sustainable Solutions for Sea Monitoring With Robotic Sailboats: N-Boat and F-Boat Twins

Alpha-N: Shortest Path Finder Automated Delivery Robot with Obstacle Detection and Avoiding System

Intelligent Selective Compliance Articulated Robot Arm robot with object recognition in a multi-agent manufacturing system

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