• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2760-2769
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• 2011

An intelligent autonomous robot generates a plan to achieve a goal. A plan is a sequence of robot actions that accomplish a given mission by being successfully executed. However, in the complex and dynamic real world, a robot may encounter unexpected situations and may not execute its planned actions any more. Therefore, an intelligent autonomous robot must prepare an efficient handling process to cope with these situations to successfully complete a given mission. Plan repair with milestone states is an efficient method to cope with the situation. It retains the advantages of other plan repair procedures. This paper proposes a regressive method of formulating milestone states and a method of assigning weighting values on conditions that compose a milestone state. The task to repair a plan may employ the weighting values as its job priority. The regressive method formulates less complex milestone states and leads to the conditions of a milestone state to take pertinent weighting values for an efficient handling procedure to repair a plan with milestone states.

• ETRI Journal
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• v.44 no.2
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• pp.183-193
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• 2022

Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multilayered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4 months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.137-143
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• 2009

Through the development of techniques, robots are becomes smaller, and many of robots needed for application are greater and greater. Method of coordinating large number of autonomous robots through local interactions has becoming an important research issue in robot community. Swarm Robot System is a system that independent autonomous robots in the restricted environment infer their status from preassigned conditions and operate their jobs through the coorperation with each other. Within the SRS,a robot contains sensor part to percept the situation around them, communication part to exchange information, and actuator part to do a work. Specially, in order to cooperate with other robots, communicating with other robot is one of the essential elements. In such as Bluetooth has many adventages such as low power consumption, small size module package, and various standard procotols, it is rated as one of the efficent communcating system for autonomous robot is developed in this paper. and How to construct and what kind of procedure to develop the communicatry system for group behavior of the SRS under intelligent space is discussed in this paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.311-317
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• 2010

In the paper, we propose an improved mobility method of modular robots by physical docking in the uneven environments. The modular robot system consists of autonomous docking device, 3 DOF robotic arm, motion controller, and main controller. Real-time location and direction of the robot are estimated using inner GPS and they are used to control direction and path of each robot for physical docking between modular robots. We design a navigation algorithm of modular robot using physical docking and cooperative navigation in the environment with broken road and low stair. The proposed method is verified by navigation experiments of three developed modular robots in the uneven environments.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.134-141
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• 2003

A major research issue associated with service robots is the creation of an environment recognition system for mobile robot navigation that is robust and efficient on various environment situations. In recent years, intelligent autonomous mobile robots have received much attention as the types of service robots for serving people and industrial robots for replacing human. To help people, robots must be able to sense and recognize three dimensional space where they live or work. In this paper, we propose a three dimensional environmental modeling method based on an edge enhancement technique using a planar fitting method and a neural network technique called "Growing Neural Gas Network." Input data pre-processing provides probabilistic density to the input data of the neural network, and the neural network generates a graphical structure that reflects the topology of the input space. Using these methods, robot's surroundings are autonomously clustered into isolated objects and modeled as polygon patches with the user-selected resolution. Through a series of simulations and experiments, the proposed method is tested to recognize the environments surrounding the robot. From the experimental results, the usefulness and robustness of the proposed method are investigated and discussed in detail.in detail.

• Journal of IKEEE
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• v.22 no.2
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• pp.440-445
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• 2018

The work presented in this paper deals with a navigation problem for a multiple mobile robots in unknown dynamic environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots' bodies must be used to detect information about the surroundings. In order to guide the robots along collision-free paths to reach their goal positions, a navigation method based on a combination of primary strategies has been developed. Most of these strategies are achieved by means of fuzzy logic controllers, and are uniformly applied in every robot. In order to improve the performance of the proposed fuzzy logic, the genetic algorithms were used to evolve the membership functions and rules set of the fuzzy controller. The simulation experiments verified that the proposed method effectively addresses the navigation problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.236-241
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• 2015

This paper presents a study on transformable multiple quadruped robots by docking between robots and waist joints. This robot is able to go on a variety of angles because of mecanum wheels. It is also a hybrid design which allows robot use legs to overcome obstacles on complex terrains and wheels to move on flat ground. The robot is applied kinematics of mecanum wheels and walking, and its walking is based on specific patterns. Docking module is located in front and backside of robot, docking algorithm is suggested and fulfilled for docking between 2 robots. A waist joint is at the center of robot body for transformation and after docking and transformation, robot can activate new functions that carry something.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.164-170
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• 2004

This paper proposes a Distributed Autonomous Robotic System(AIS) based on Artificial Immune System(AIS) and Distributed Genetic Algorithm(DGA). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: dispersion and aggregation. AIS decides one among above two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the DGA in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.46-50
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• 2013

This paper proposes an adaptive fault accommodation control approach for flexible-joint (FJ) robots with multiple actuator faults. It is assumed that the value and occurrence time of multiple actuator faults are unknown. An adaptive fault accommodation control scheme with prescribed performance bounds, which characterize the convergence rate and maximum overshoot of tracking errors, is designed to accommodate the actuator faults. From the Lyapunov stability theorem, it is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded and tracking errors are preserved within prescribed performance bounds regardless of actuator faults.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.699-704
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• 2004

This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) and a Classifier System(CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.