4,694 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
A Multiagent Architecture for Mobile Robot Navigation Using Hierarchical Fuzzy and Sliding Mode Controllers
The challenge of this work is to implement an algorithm which enables the robot to achieve independent activities in the purpose of achieving a common goal, which consists in autonomous navigation in a partially unknown environment. The use of multiagent system is convenient for such a problem. Hence, we have designed a structure composed of four agents dedicated to perception, navigation, static, and dynamic obstacle avoidance. Those agents interact through a coordination system
An hybridization of global-local methods for autonomous mobile robot navigation in partially-known environments
This paper deals with the navigation problem of an autonomous non-holonomic mobile robot in partially-known environment. In this proposed method, the entire process of navigation is divided into two phases: an off-line phase on which a distance-optimal reference trajectory enables the mobile robot to move from an initial position to a desired target which is planned using the B-spline method and the Dijkstra algorithm. In the online phase of the navigation process, the mobile robot follows the planned trajectory using a sliding mode controller with the ability of avoiding unexpected obstacles by the use of fuzzy logic controller. Also, the fuzzy logic and fuzzy wall-following controllers are used to accomplish the reactive navigation mission (path tracking and obstacle avoidance) for a comparative purpose. Simulation results prove that the proposed path planning method (B-spline) is simple and effective. Also, they attest that the sliding mode controller track more precisely the reference trajectory than the fuzzy logic controller (in terms of time elapsed to reach the target and stability of two wheels velocity) and this last gives best results than the wall-following controller in the avoidance of unexpected obstacles. Thus, the effectiveness of our proposed approach (B-spline method combined with sliding mode and fuzzy logic controllers) is proved compared to other techniques
Decentralized Autonomous Navigation Strategies for Multi-Robot Search and Rescue
In this report, we try to improve the performance of existing approaches for
search operations in multi-robot context. We propose three novel algorithms
that are using a triangular grid pattern, i.e., robots certainly go through the
vertices of a triangular grid during the search procedure. The main advantage
of using a triangular grid pattern is that it is asymptotically optimal in
terms of the minimum number of robots required for the complete coverage of an
arbitrary bounded area. We use a new topological map which is made and shared
by robots during the search operation. We consider an area that is unknown to
the robots a priori with an arbitrary shape, containing some obstacles. Unlike
many current heuristic algorithms, we give mathematically proofs of convergence
of the algorithms. The computer simulation results for the proposed algorithms
are presented using a simulator of real robots and environment. We evaluate the
performance of the algorithms via experiments with real robots. We compare the
performance of our own algorithms with three existing algorithms from other
researchers. The results demonstrate the merits of our proposed solution. A
further study on formation building with obstacle avoidance for a team of
mobile robots is presented in this report. We propose a decentralized formation
building with obstacle avoidance algorithm for a group of mobile robots to move
in a defined geometric configuration. Furthermore, we consider a more
complicated formation problem with a group of anonymous robots; these robots
are not aware of their position in the final configuration and need to reach a
consensus during the formation process. We propose a randomized algorithm for
the anonymous robots that achieves the convergence to a desired configuration
with probability 1. We also propose a novel obstacle avoidance rule, used in
the formation building algorithm.Comment: arXiv admin note: substantial text overlap with arXiv:1402.5188 by
other author
Cellular Automata Applications in Shortest Path Problem
Cellular Automata (CAs) are computational models that can capture the
essential features of systems in which global behavior emerges from the
collective effect of simple components, which interact locally. During the last
decades, CAs have been extensively used for mimicking several natural processes
and systems to find fine solutions in many complex hard to solve computer
science and engineering problems. Among them, the shortest path problem is one
of the most pronounced and highly studied problems that scientists have been
trying to tackle by using a plethora of methodologies and even unconventional
approaches. The proposed solutions are mainly justified by their ability to
provide a correct solution in a better time complexity than the renowned
Dijkstra's algorithm. Although there is a wide variety regarding the
algorithmic complexity of the algorithms suggested, spanning from simplistic
graph traversal algorithms to complex nature inspired and bio-mimicking
algorithms, in this chapter we focus on the successful application of CAs to
shortest path problem as found in various diverse disciplines like computer
science, swarm robotics, computer networks, decision science and biomimicking
of biological organisms' behaviour. In particular, an introduction on the first
CA-based algorithm tackling the shortest path problem is provided in detail.
After the short presentation of shortest path algorithms arriving from the
relaxization of the CAs principles, the application of the CA-based shortest
path definition on the coordinated motion of swarm robotics is also introduced.
Moreover, the CA based application of shortest path finding in computer
networks is presented in brief. Finally, a CA that models exactly the behavior
of a biological organism, namely the Physarum's behavior, finding the
minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From
software to wetware. Springer, 201
Motion planning and assembly for microassembly workstation
In general, mechatronics systems have no standard
operating system that could be used for planning and
control when these complex devices are running. The
goal of this paper is to formulate a work platform that can
be used as a method for obtaining precision in the
manipulation of micro-entities using micro-scale
manipulation tools for microsystem applications. This
paper provide groundwork for motion planning and
assembly of the Micro-Assembly Workstation (MAW)
manipulation system. To demonstrate the feasibility of the
idea, the paper implements some of the motion planning
algorithms; it investigates the performance of the
conventional Euclidean distance algorithm (EDA),
artificial potential fields’ algorithm, and A* algorithm
when implemented on a virtual space
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