255 research outputs found
Formation of Multiple Groups of Mobile Robots Using Sliding Mode Control
Formation control of multiple groups of agents finds application in large
area navigation by generating different geometric patterns and shapes, and also
in carrying large objects. In this paper, Centroid Based Transformation (CBT)
\cite{c39}, has been applied to decompose the combined dynamics of wheeled
mobile robots (WMRs) into three subsystems: intra and inter group shape
dynamics, and the dynamics of the centroid. Separate controllers have been
designed for each subsystem. The gains of the controllers are such chosen that
the overall system becomes singularly perturbed system. Then sliding mode
controllers are designed on the singularly perturbed system to drive the
subsystems on sliding surfaces in finite time. Negative gradient of a potential
based function has been added to the sliding surface to ensure collision
avoidance among the robots in finite time. The efficacy of the proposed
controller is established through simulation results.Comment: 8 pages, 5 figure
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
UAV based group coordination of UGVs
Coordination of autonomous mobile robots has received significant attention during the last two decades with the emergence of small, lightweight and low power embedded systems. Coordinated motion of heterogenous robots is important due to the fact that unique advantages of di erent robots might be combined to increase the overall task efficiency of the system. In this thesis, a new coordination framework is developed for a heterogeneous robot system, composed of multiple Unmanned Ground Vehicles (UGVs) and an Unmanned Aerial Vehicle (UAV), that operates in an environment where individual robots work collaboratively in order to accomplish a predefined goal. UAV, a quadrotor, detects the target in the environment and provides a feasible trajectory from an initial configuration to a final target location. UGVs, a group of nonholonomic wheeled mobile robots, follow a virtual leader which is created as the projection of UAV's 3D position onto the horizontal plane. The UAV broadcasts its position at certain frequency to all UGVs. Two different coordination models are developed. In the dynamic coordination model, reference trajectories for each robot is generated from the motion of nodal masses located at each UGV and connected by virtual springs and dampers. Springs have adaptable parameters that allow the desired formation to be achieved In the kinematic coordination model, the position of the virtual leader and distances from the two closest neighbors are directly utilized to create linear and angular velocity references for each UGV. Several coordinated tasks are presented and the results are verified by simulations where different number of UGVs are employed and certain amount of communication delays between the vehicles are also considered. Simulation results are quite promising and form a basis for future experimental work on the topic
Formation Control for a Fleet of Autonomous Ground Vehicles: A Survey
Autonomous/unmanned driving is the major state-of-the-art step that has a potential to fundamentally transform the mobility of individuals and goods. At present, most of the developments target standalone autonomous vehicles, which can sense the surroundings and control the vehicle based on this perception, with limited or no driver intervention. This paper focuses on the next step in autonomous vehicle research, which is the collaboration between autonomous vehicles, mainly vehicle formation control or vehicle platooning. To gain a deeper understanding in this area, a large number of the existing published papers have been reviewed systemically. In other words, many distributed and decentralized approaches of vehicle formation control are studied and their implementations are discussed. Finally, both technical and implementation challenges for formation control are summarized
Navigational Path Analysis of Mobile Robot in Various Environments
This dissertation describes work in the area of an autonomous mobile robot. The objective is navigation of mobile robot in a real world dynamic environment avoiding structured and unstructured obstacles either they are static or dynamic. The shapes and position of obstacles are not known to robot prior to navigation. The mobile robot has sensory recognition of specific objects in the environments. This sensory-information provides local information of robots immediate surroundings to its controllers. The information is dealt intelligently by the robot to reach the global objective (the target). Navigational paths as well as time taken during navigation by the mobile robot can be expressed as an optimisation problem and thus can be analyzed and solved using AI techniques. The optimisation of path as well as time taken is based on the kinematic stability and the intelligence of the robot controller. A successful way of structuring the navigation task deals with the issues of individual behaviour design and action coordination of the behaviours. The navigation objective is addressed using fuzzy logic, neural network, adaptive neuro-fuzzy inference system and different other AI technique.The research also addresses distributed autonomous systems using multiple robot
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