665 research outputs found
SHARED CONTROL FOR MOBILE ROBOT OBSTACLE AVOIDANCE
The use of robots has become more prevalent in the last several decades in many sectors such
as manufacturing, research, and consumer use [18]. With such varying environments and requirements of these robots it has become increasingly important to develop systems capable of adapting
and ensuring safety of the robot and surroundings. This study examines shared control as a method
of obstacle avoidance for mobile robots.
Shared control makes use of multiple control modes to obtain desired properties from each.
This lends a wide range of applications of shared control, from assisted wheelchair operation [37]
to autonomous vehicle navigation [10]. Shared control allows for highly versatile controllers and
enables easier interfacing with humans.
In this thesis we propose control strategies for two mobile robots: a kinematic non-holonomic
wheeled robot and a dynamic quad-rotor. Lyapunov analysis is used to show stability of the systems while accounting for shared control switching. With the shared control architecture, it is
proven the robots always avoid collision with obstacles. The theoretical analysis is validated with
experiments which show promising results and motivate shared control as a viable solution for safe
navigation in other systems
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
深層強化学習を用いた動的環境下における事前知識不要なロボットナビゲーションに関する研究
Tohoku University博士(工学)thesi
A Fuzzy Logic Controller for Autonomous Wheeled Vehicles
Autonomous vehicles have potential applications in many fields, such as replacing humans in hazardous environments, conducting military missions, and performing routine tasks for industry. Driving ground vehicles is an area where human performance has proven to be reliable. Drivers typically respond quickly to sudden changes in their environment. While other control techniques may be used to control a vehicle, fuzzy logic has certain advantages in this area; one of them is its ability to incorporate human knowledge and experience, via language, into relationships among the given quantities. Fuzzy logic controllers for autonomous vehicles have been successfully applied to address various (and sometimes simultaneous) navigational issues
Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots
Safe robot navigation is a fundamental research field for autonomous robots
including ground mobile robots and flying robots. The primary objective of a
safe robot navigation algorithm is to guide an autonomous robot from its
initial position to a target or along a desired path with obstacle avoidance.
With the development of information technology and sensor technology, the
implementations combining robotics with sensor network are focused on in the
recent researches. One of the relevant implementations is the sensor network
based robot navigation. Moreover, another important navigation problem of
robotics is safe area search and map building. In this report, a global
collision-free path planning algorithm for ground mobile robots in dynamic
environments is presented firstly. Considering the advantages of sensor
network, the presented path planning algorithm is developed to a sensor network
based navigation algorithm for ground mobile robots. The 2D range finder sensor
network is used in the presented method to detect static and dynamic obstacles.
The sensor network can guide each ground mobile robot in the detected safe area
to the target. Furthermore, the presented navigation algorithm is extended into
3D environments. With the measurements of the sensor network, any flying robot
in the workspace is navigated by the presented algorithm from the initial
position to the target. Moreover, in this report, another navigation problem,
safe area search and map building for ground mobile robot, is studied and two
algorithms are presented. In the first presented method, we consider a ground
mobile robot equipped with a 2D range finder sensor searching a bounded 2D area
without any collision and building a complete 2D map of the area. Furthermore,
the first presented map building algorithm is extended to another algorithm for
3D map building
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