• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.130-134
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• 1992

The ability of a robot system to comply to an environment via the control of tool-environment interaction force is of vital for the successful task accomplishment in many robot application. This paper presents the implementation of external force control for two dimensional contour following task using a commercial robot system. Force accommodation is used since a constraint imposed in our work is not to modify the commercial robot system. A linear, decoupled model of two dimensional contour following system in the discrete time domain is derived first. Then the experimental verification of linear control is obtained using a PUMA 560 manipulator with standard Unimation controller, Astek FS6-120A six axis wrist force sensor attached externally to the arm and LSI-11173 microcomputer. Experimentally obtained data shows that the RMS contact force error is 0.8246 N when following the straight edge and 2.3768 N when following 40 mm radius curved contour.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.246-257
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• 2010

Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2154-2159
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• 2005

This paper presents the kinematic analysis of two robots, an exoskeleton type master robot and a human like slave robot with two arms. Two robots are designed and built to be equivalent as motion following robots. The operator wears the exoskeleton robot to generate motions, then the slave robot is required to follow after the motion of the master robot. However, different kinematic configuration yields position mismatches of the end-effectors. To synchronize motions of two robots, kinematic analysis of mapping is analyzed. The forward and inverse kinematics have been simulated and the corresponding experiments are also conducted to confirm the proposed mapping analysis.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.5-8
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• 2002

In this paper, we propose the self-autonomous algorithm for mobile robot system. The proposed mobile robot system controlled by Personal Digital Assistant(PDA) can follow the target at regular intervals. The mobile robot can evaluate the distance between robot and target with ultrasonic sensors, transmits the distance to the PDA. The velocity and direction decided in PDA are transmitted to the mobile robot with wireless LAN communication. Considering the state, velocity-changing and distance-maintenance, of the mobile robot, driving velocity and direction are applied. For safety, the velocity of the mobile robot is changed step by step. As a result, we confirm the ability of following the target with proposed mobile robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.287-292
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• 2003

The ability of robot is being various and complex. The robot is utilizing distance, image data and voice data for sensing its circumstance. This paper suggests the 2-layer fuzzy control as the algorithm that control robot with various sensor information. In a obstacle avoidance, it utilizes many range finders and classifies them into 3parts(front, left, right). In 3 sub-controllers, the controller executes fuzzy conference. And then it executes combined control with a combination of outputs of 3 sub-controllers in the second step. The text compares the 2-layer fuzzy controller with the hierarchical fuzzy controller that has analogous structure. And the performance of the 2-layer fuzzy controller is confirmed by application this controller to robot following, simulation to each other and real experiment.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2142-2148
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• 2015

This paper proposes novel real-time footstep planning and following methods for the navigation of humanoid robots. A footstep command is defined by a walking direction and step lengths for footstep planning. The walking direction is determined by a uni-vector field navigation method, and the allowable yawing range caused by hardware limitation is considered. The lateral step length is determined to avoid collisions between the two legs while walking. The sagittal step length is modified by a binary search algorithm when collision occurs between the robot body and obstacles in a narrow space. If the robot body still collides with obstacles despite the modification of the sagittal step length, the lateral step length is shifted at the next footstep. For footstep following, a walking pattern generator based on a 3-D linear inverted pendulum model is utilized, which can generate modifiable walking patterns using the zero-moment point variation scheme. Therefore, it enables a humanoid robot to follow the footstep command planned for each footstep. The effectiveness of the proposed method is verified through simulation and experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.476-480
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• 2012

In this paper, artificial potential field(APF) is applied to formation control for the leader-following swarm robot. Furthermore, APF is constructed by applying the electrical field model. Moreover, to model the obstacle effectively, each obstacle has different form due to the electrical field equation. The proposed method is formed as two sub-objective: path planning for the leader-robot and following-robots following the leader-robot. Finally, simulation example is given to prove the validity of proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.161.4-161
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• 2001

This paper presents adaptive control of robot manipulator using neuro-fuzzy controller Fuzzy logic is control incorrect system without correct mathematical modeling. And, neural network has learning ability, error interpolation ability of information distributed data processing, robustness for distortion and adaptive ability. To reduce the number of fuzzy rules of the FLS(fuzzy logic system), we consider the properties of robot dynamic. In fuzzy logic, speciality and optimization of rule-base creation using learning ability of neural network. This paper presents control of robot manipulator using neuro-fuzzy controller. In proposed controller, fuzzy input is trajectory following error and trajectory following error differential ...

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.101-110
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• 2004

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, humans and robots need to be in close proximity to each other as much as possible. Moreover, it is necessary for their interactions to occur naturally. It is desirable for a robot to carry out human following, as one of the human-affinitive movements. The human-following robot requires several techniques: the recognition of the moving objects, the feature extraction and visual tracking, and the trajectory generation for following a human stably. In this research, a predictable intelligent space is used in order to achieve these goals. An intelligent space is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to follow the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and following of the walking human with the mobile robot are presented.

• Journal of IKEEE
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• v.17 no.1
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• pp.44-50
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• 2013

This paper proposed the implementation of haptic-based robot which is following a human by using fundamental sensors on robot arms without additional sensors. Joints in the robot arms have several motors, and their angles can be read out by these motors when a human pushes or pulls the robot arms. So these arms can be used as haptic sensors. The implemented robot follows a human by interacting with robot arms and human hands, as a human follows a human by hands.