• Journal of the Korea Society for Simulation
• /
• v.18 no.4
• /
• pp.49-58
• /
• 2009

Top-down approach in the intelligent robot research has focused on the single object intelligence however, it has two weaknesses. One is that has a high cost and a long spending time of sensing, calculating and communications. The other is the difficulty of responding to react changes in the unpredictable environment. we propose the collective intelligence algorithm based on Bottom-up approach for improving these weaknesses and the applied agent model and verify by simulation. The Modified Flocking Algorithm proposed in this research is the algorithm which is modified version of the concept of the Flocking (Craig Reynolds) which is used to model the flocks, herds, and schools in the graphics or games, and simplified the operation of conventional Flocking algorithm to make it easy to apply for the number of group robots. We modeled the Boid agent and verified possibility collectivization of the Modified Flocking Algorithm by simulation. And We validated by the actual multiple mobile robot experiment.

• Korean Journal of Computational Design and Engineering
• /
• v.10 no.5
• /
• pp.339-348
• /
• 2005

In this paper, LOD (Level Of Detail) for flocking, which is the real-time simulation on the movement or some groups such as fighting soldiers, moving fishes and flying birds, is presented. And a flocking LOD algorithm that uses factors such as the speed of fish, direction, and shape is proposed. Model data is modified for LOD in advance, so as to reduce strange edge collapse and unwanted holes. The errors of model data were identified by transforming polygonal model into octree-based cubes and revised before rendering. Experimental results show that the proposed algorithm considering flocking characteristics shows fast frame rates as compared with the conventional continuous LOD algorithm.

• Journal of Korea Game Society
• /
• v.11 no.5
• /
• pp.23-30
• /
• 2011

Flocking behaviors are frequently used in games and computer graphics for realistic simulation of massive crowds. Since simulation of massive crowds in real time is a computationally intensive task, there were many researches on efficient algorithm. In this paper, we find experimentally the fact that there are unnecessary computations in the previous efficient flocking algorithm, and propose a noble algorithm that overcomes the weakness of the previous algorithm with a simple heuristic. A number of experiments were conducted to evaluate the performance of the proposed algorithm. The experimental results showed that the proposed algorithm outperformed the previous efficient algorithm by about 21% on average.

• Journal of the Korea Society for Simulation
• /
• v.19 no.4
• /
• pp.1-9
• /
• 2010

In this paper, advanced evacuation analysis simulation on a passenger ship is performed. Velocity based model has been implemented and used to calculate the movement of the individual passengers under the evacuation situation. The age and gender of each passenger are considered as the factors of walking speed. Flocking algorithm is applied for the passenger's group behavior. Penalty walking velocity is introduced to avoid collision between the passengers and obstacles, and to prevent the position overlap among passengers. Application of flocking algorithm and penalty walking velocity to evacuation simulation is verified through implementation of the 11 test problems in IMO (International Maritime Organization) MSC (Maritime Safety Committee) Circulation 1238.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.12
• /
• pp.2937-2943
• /
• 2013

This paper introduces a real-time flocking simulation framework through radial basis function(RBF). The proposed framework first divides the entire environment into a grid structure and then assign a vector per each cell. These vectors are automatically calculated by using RBF function, which is parameterized from user-input control lines. Once the construction of vector field is done, then, flocks determine their path by following the vector field flow. The collision with static obstacles are modeled as a repulsive vector field, which is ultimately over-layed on the existing vector field and the inter-individual collision is also handled through fast lattice-bin method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.10
• /
• pp.1873-1880
• /
• 2016

Most of the energy used to operate a cellular network is consumed by a base station (BS), and reducing the transmission power of a BS is required for energy-efficient cellular networks. In this paper, a distributed transmit power control (TPC) algorithm is proposed based on the flocking model to improve the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm each mobile station (MS) in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking model and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases. Consequently, it significantly improves the energy efficiency of a cellular network.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.48 no.6
• /
• pp.419-429
• /
• 2020

In conducting a mission to explore and track targets using a number of unmanned aerial vehicles(UAVs), performance for that mission may vary significantly depending on the operating conditions of the UAVs such as the number of operations, the altitude, and what future flight paths each aircraft decides based on its current position. However, studies on the number of operations, operating conditions, and flight patterns of unmanned aircraft in these surveillance missions are insufficient. In this study, several types of flight simulations were conducted to detect and determine targets while multiple UAVs were involved in the avoidance of collisions according to various autonomous flight algorithms based by flocking theory, and the results were presented to suggest a more efficient/effective way to control a number of UAVs in target detection missions.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39A no.8
• /
• pp.488-490
• /
• 2014

This paper deals with distributed time and frequency synchronization algorithms using the flocking technique for OFDMA-based wireless mesh networks. We propose a time and frequency synchronization model taking into account channel propagation delays existing in wireless mesh networks, and analyze the convergence condition of the proposed synchronization algorithm. Convergence performance of the proposed synchronization algorithm is analyzed via computer simulation in terms of synchronization parameters in the time and frequency synchronization model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.499-502
• /
• 2018

We propose a wireless-powered multihop transmission scheme using inter-node cooperation in a linear network topology. The proposed protocol determines the energy transfer time for each node to make the lifetime of the each node be equal in order to maximize the lifetime of the multihop path. To make the lifetime of each node the same, we apply the flocking algorithm which imitates the behavior of a bird flock flying at the same velocity, so that the lifetime of the nodes is averaged locally. Simulation results show that the proposed algorithm can maximize the lifetime of the multihop path by making all nodes have the same lifetime.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2186-2188
• /
• 1998

In this paper, Fundamental rules governing group intelligence "arrangement" behavior of multiple number of autonomous mobile robots are represented by a small number of fuzzy rules. Complex lifelike behavior is considered as local interactions between simple individuals under small number of fundamental rules. The fuzzy rules for arrangement are generated from clustering the input-output data obtained from the arrangement algorithm. Simulation shows the fuzzy rules successfully realizes fundamental rules of the flocking group behavior.