3,190 research outputs found
Comprehensive review on controller for leader-follower robotic system
985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies
aColor: Mechatronics, Machine Learning, and Communications in an Unmanned Surface Vehicle
The aim of this work is to offer an overview of the research questions,
solutions, and challenges faced by the project aColor ("Autonomous and
Collaborative Offshore Robotics"). This initiative incorporates three different
research areas, namely, mechatronics, machine learning, and communications. It
is implemented in an autonomous offshore multicomponent robotic system having
an Unmanned Surface Vehicle (USV) as its main subsystem. Our results across the
three areas of work are systematically outlined in this paper by demonstrating
the advantages and capabilities of the proposed system for different Guidance,
Navigation, and Control missions, as well as for the high-speed and long-range
bidirectional connectivity purposes across all autonomous subsystems.
Challenges for the future are also identified by this study, thus offering an
outline for the next steps of the aColor project.Comment: Paper was originally submitted to and presented in the 8th Transport
Research Arena TRA 2020, April 27-30, 2020, Helsinki, Finlan
TRIDENT: A Framework for Autonomous Underwater Intervention
TRIDENT is a STREP project recently approved by the European Commission whose proposal
was submitted to the ICT call 4 of the 7th Framework Program. The project proposes a new methodology
for multipurpose underwater intervention tasks. To that end, a cooperative team formed with an
Autonomous Surface Craft and an Intervention Autonomous Underwater Vehicle will be used. The
proposed methodology splits the mission in two stages mainly devoted to survey and intervention tasks,
respectively. The project brings together research skills specific to the marine environments in navigation
and mapping for underwater robotics, multi-sensory perception, intelligent control architectures, vehiclemanipulator
systems and dexterous manipulation. TRIDENT is a three years project and its start is planned
by first months of 2010.This work is partially supported by the European Commission
through FP7-ICT2009-248497 projec
An Autonomous Surface Vehicle for Long Term Operations
Environmental monitoring of marine environments presents several challenges:
the harshness of the environment, the often remote location, and most
importantly, the vast area it covers. Manual operations are time consuming,
often dangerous, and labor intensive. Operations from oceanographic vessels are
costly and limited to open seas and generally deeper bodies of water. In
addition, with lake, river, and ocean shoreline being a finite resource,
waterfront property presents an ever increasing valued commodity, requiring
exploration and continued monitoring of remote waterways. In order to
efficiently explore and monitor currently known marine environments as well as
reach and explore remote areas of interest, we present a design of an
autonomous surface vehicle (ASV) with the power to cover large areas, the
payload capacity to carry sufficient power and sensor equipment, and enough
fuel to remain on task for extended periods. An analysis of the design and a
discussion on lessons learned during deployments is presented in this paper.Comment: In proceedings of MTS/IEEE OCEANS, 2018, Charlesto
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