• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.429-434
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• 2013

This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.161-166
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• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.

• ETRI Journal
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• v.45 no.5
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• pp.836-846
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• 2023

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.69-78
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• 2009

Localization is a very important technique for the mobile robot to navigate in outdoor environment. In this paper, the development of the sensor fusion algorithm for controlling mobile robots in outdoor environments is presented. The multi-sensorial dead-reckoning subsystem is established based on the optimal filtering by first fusing a heading angle reading data from a magnetic compass, a rate-gyro, and two encoders mounted on the robot wheels, thereby computing the dead-reckoned location. These data and the position data provided by a global sensing system are fused together by means of an extended Kalman filter. The proposed algorithm is proved by simulation studies of controlling a mobile robot controlled by a backstepping controller and a cascaded controller. Performances of each controller are compared.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.722-730
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• 2008

This paper proposes two novel algorithms enabling mobile robots to cooperate with each other in a reliability-based system and a time-critical system. In the reliability-based cooperative system, the concepts of a mobile ad hoc network (MANET) and an object entropy are adopted in order to coordinate a specific task. A logical robot group is created based on the exchange of request and reply messages in a robot communication group whose organization depends on transmission range. In the time-critical cooperative system, relational entropy is used to define the relationship between mobile robots. A group leader is selected based on optimizing power consumption. The proposed algorithm has been verified based on the computer-based simulation and soccer robot experiment. The performance metrics are defined. The metrics include the number of messages needed to make a logical robot group and to obtain the relationship of robots and the power consumption to select a group leader. They are verified by simulation and experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1447-1456
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• 2011

In this paper, we propose a T-S fuzzy feedback linearization method for controlling a non-linear system with multi-input, and the method is applied for trajectory tracking control of wheeled mobile robot. First, an error dynamic equation of wheeled mobile robot is represented by a T-S fuzzy model, and then the T-S fuzzy model is transformed to a linear control system through the nonlinear fuzzy coordinate change and the nonlinear state feedback input. Simulation results showed that the trajectory tracking controller by using the proposed multi-input feedback linearization method gives better performance than the trajectory tracking controller by using the PDC(Parallel Distributed Compensation) method for controlling the T-S Fuzzy system.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.52-57
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• 2014

This paper presents an implementation of a smooth path planning method considering physical limits on a real time operating system for a two-wheel mobile robot. A Bezier curve is utilized to make a smooth path considering a robot's position and direction angle through the defined path. A convolution operator is used to generate the center velocity trajectory to travel the distance of the planned path while satisfying the physical limits. The joint space velocity is computed to drive the two-wheel mobile robot from the center velocity. Trajectory planning, velocity command according to the planned trajectory, and monitoring of encoder data are implemented with a multi-tasking system. And the synchronization of tasks is performed with a real-time mechanism of Event Flag. A real time system with multi-tasks is implemented and the result is compared with a non-real-time system in terms of path tracking to the designed path. The result shows the usefulness of a real-time multi-tasking system to the control system which requires real-time features.

• The Journal of Korea Robotics Society
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• v.7 no.1
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• pp.45-56
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• 2012

This paper proposes how to improve the performance of CSS-based indoor localization system. CSS based localization utilizes signal flight time between anchors and tag to estimate distance. From the distances, the 3-dimensional position is calculated through trilateration. However the error in distance caused from multi-path effect transfers to the position error especially in indoor environment. This paper handles a problem of reducing error in raw distance information. And, we propose the new localization method by pattern matching instead of the conventional localization method based on trilateration that is affected heavily on multi-path error. The pattern matching method estimates the position by using the fact that the measured data of near positions possesses a high similarity. In order to gain better performance of localization, we use EKF(Extended Kalman Filter) to fuse the result of CSS based localization and robot model.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.106-111
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• 2008

This paper presents a decentralized coordination for a small-scale mobile robot teams performing a task through cooperation. Robot teams are required to generate and maintain various geometric patterns adapting to an environment and/or a task in many cooperative applications. In particular, all robots must continue to strive toward achieving the team's mission even if some members fail to perform their role. Toward this end, given the number of robots in a team, an effective coordination is investigated for decentralized formation control strategies. Specifically, all members are required first to reach agreement on their coordinate system and have an identifier (ID) for role assignment in a self-organizing way. Then, employing IDs on individual robots within a common coordinate system, a decentralized neighbor-referenced formation control is realized to generate, keep, and switch between different geometric shapes. This approach is verified using an in-house simulator and physical mobile robots. We detail and evaluate the formation control approach, whose common features include self-organization, robustness, and flexibility.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.468-472
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• 1992

In recent years, lots of researches on autonomous mobile robot have been accomplished. However they focused on environment recognition and its processing to make a decision on the motion, And cooperative multi-robot, which must be able to avoid crash and to make mutual communication, has not been studied much. This paper deals with cooperative motion of two robots, 'Meari 1" and "Meari 2 " made in our laboratory, based on communication between the two. Because there is an interference on communication occurring in cooperative motion of multi-robot, many restrictive conditions are required. Therefore, we have designed these robot system so that communication between them is available and mutual interference is precluded, and we used fuzzy interference to overcome unstability of sensor data.of sensor data.