• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.105-111
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• 2009

In this paper, we provide experimental results and verification for obstacle avoidance algorithm 'ELA(Emergency Level Around)', which is applicable to rescue robots. ELA is a low level intelligence-based obstacle avoidance algorithm, so can be used in fast mobile robots requiringhigh speed in operation with little computational load. Constructed system for experiments consist of laptop, sensors, peripheral devices and mobile robot platform VSTR(Variable Single-tracked Robot) to realize predetermined scenarios. Finally, experiment was conducted in indoor surroundings including miscellaneous things as well as dark environment to show fitness and robustness of ELA for rescue, and it is shown that VSTR navigates endowed area well with real-time obstacle avoidance based on ELA. Therefore, it is concluded that ELA can be a candidate algorithm to increase mobility of rescue robots in real situation.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.658-663
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• 2012

An accurate outdoor localization method using line/arc features is suggested for mobile robots with LRFs (Laser Range Finders) and odometry. Localization is a key process for outdoor mobile robots which are used for autonomous navigation, exploration and so on. In this paper, an accurate pose correction algorithm is proposed for mobile robots using LRFs, which use three feature types: line, circle, and arc. Using this method we can reduce the number of singular cases that robots couldn't find their pose. Finally we have got simulation results to validate the proposed algorithm.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.819-824
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• 1997

This paper presents a cell-based motion control strategy for soccer playing mobile robots. In the central robot motion planner, the planar ground is divided into rectangular cells with variable sizes and motion indices to which direction the mobile robot should move. At every time the multiple objects-the goal gate, ball, and robots-detected, integer values of motion indices are assigned to the cells occupied by mobile robots. Once the indices being calculated, the most desirable state-action pair is chosen from the state and action sets to achieve successful soccer game strategy. The proposed strategy is computationally simple enough to be used for fast robotic soccer system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.818-829
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• 2003

A cooperating control algorithm for two nonholonomic mobile robots is proposed. The task is composed of collision avoidance against obstacles and carrying a ladder. The front robot and the rear robot are called the leader and the follower, respectively. Each robot has a nonholonomic constraint so it cannot move in perpendicular directions. The environment is initially supposed to be unknown except target position. The torque that drives leader is determined by distance between the leader and the target position or the distance between it and the obstacles. The torque by target is attractive and the torque by obstacles is repulsive. The two mobile robots are supposed to be connected by link that can be expanded and contracted. The follower computes its torque using position and orientation information from the leader by communication. Simulation results show that the robots can drive to target position without colliding into the obstacles and maintain the distance in the allowable range.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.603-608
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• 2003

Recently, personal robots and home robots are developing by many companies and research groups. It is considered that a general effective interface for user of those robots is speech or voice. In this paper, Japanese speech based man-machine interface system is discussed for reflecting the fuzziness of natural language on robots, by using fuzzy reasoning. The present system consists of the derivation part of action command and the modification part of the derived command. In particular, a unique problem of Japanese is solved by applying the morphological analyzer ChaSen. The proposed system is applied for the motion control of a robot manipulator. It is proved from the experimental results that the proposed system can easily modify the same voice command to the actual different levels of the command, according to the current state of the robot.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.36-45
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• 1992

A numerical trajectory planning method for path-constrained trajectory planning is proposed which ensures collision-free and time-optimal motions for two robotic manipulators with limited actuator torques and velocities. For each robot, physical constraints of the robots such as limited torques or limited rotational velocities of the actuators are converted to the constraints on velocity and acceleration along the path, which is described by a scalar variable denoting the traveled distance from starting point. Collision region is determined on the coordination space according to the kinematic structures and the geometry of the paths of the robots. An Extended Coordination Space is then constructed` an element of the space determines the postures and the velocities of the robots, and all the constraints described before are transformed to some constraints on the behaviour of the coordination-velocity curves in the space. A dynamic programming technique is them provided with on the discretized Extended Coordination Space to derive a collision-free and time-optimal trajectory pair. Numerical example is included.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2717-2720
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• 2003

A mathematical framework for deriving acceleration bounds from given joint torque limits of two cooperating robots are described in this paper. Especially when the torque limits are given in 2-norm, the resultant geometrical configuration is ellipsoid(the ellipsoid is often called manipulability ellipsoid in many works). At first, the mathematical derivation starts from the dynamics of both object and robots as well as the kinematics of the robots, and is finally arranged in a form of equation relating joint torques to object acceleration through a complete constraint contact(or “very-soft contact”). To show the usefulness of the proposed method, two examples are included, and especially the case where friction effects the ellipsoid shape is also considered In the example.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.119-125
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• 2008

This paper presents the polygon-based Q-leaning and Cascade Support Vector Machine algorithm for object search with multiple robots. We organized an experimental environment with ten mobile robots, twenty five obstacles, and an object, and then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and Cascade SVM to enhance the fusion model with DBAM and ABAM process.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.918-925
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• 2017

This paper presents a path planning problem for multi-robot system in the environment with dynamic obstacles. In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly, a navigation method based on fuzzy logic controllers has been developed by using proximity sensors. There are two kinds of fuzzy controllers developed in this work, one is used for obstacle avoidance and the other is used for orientation to the target. Both static and dynamic obstacles are included in the environment and the dynamic obstacles are defined with no type of restriction of direction and velocity. Here, the environment is unknown for all the robots and the robots should detect the surrounding information only by the sensors installed on their bodies. The simulation results show that the proposed method has a positive effectiveness for the path planning problem.