• Proceedings of the KIEE Conference
• /
• 2003.11b
• /
• pp.19-22
• /
• 2003

This paper proposes an algorithm for navigation of an autonomous mobile robot with vision sensor. For obstacle avoidance, we used a curvature trajectory method. Using this method, translational and rotational speeds are controlled independently and the mobile robot traces a smooth curvature trajectory that consists of circle trajectories to a target point. While trying to avoid obstacles, the robot fan be goal-directed using curvature trajectory.

• The Journal of Korea Robotics Society
• /
• v.4 no.1
• /
• pp.43-48
• /
• 2009

Generally, underwater vehicle type of propeller shows low efficiency about 50%-55%. However, the efficiency of swimming mechanism of a fish is 60%-70%, more efficient about 20% than screw propellers. Recently, research of underwater vehicle type of fish increase due to its good efficiency and is regarded as a typical bio-mimical robot. In this research, a new algorithm and mechanism that show low energy consumption imitating swimming mechanism of fish proposed increasing speed and running time in field trial.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.543-547
• /
• 2005

In this paper, we designed a intelligent autonomous driving robot by using Fuzzy algorithm. The object of designed robot is recognition of obstacle, avoidance of obstacle and safe arrival. We append a suspension system to auxiliary wheel for improvement in stability and movement. The designed robot can arrive at destination where is wanted to go by the old and the weak and the handicapped at indoor hospital and building.

• Proceedings of the IEEK Conference
• /
• 2002.06e
• /
• pp.29-32
• /
• 2002

In this paper the wheeled mobile robot is studied. The kinematic and dynamic modeling of the robot is presented via LPD(Linear Parameter Dependent) framework. A path-planning algorithm which is optimized in the sense of robot mobility and distance is presented. And by using PI controller we show that the presented algorithm and model is work very well in the computer simulation and experiment.

• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.10
• /
• pp.25-31
• /
• 1995

In this paper, a direct drive scalar robot manipulator is constructed and its mechanical machanism for operation is explained. Also, a motion controller board for the direct drive robot manipulator was developed where the IBM 486 computer is the main controller. For the developed direct drive robot, a force/motion control algorithm based on an active compliance scheme is developed. A preliminary experiment using the developed direct drive for a peg-in-hole job was done by implementing the control algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.8
• /
• pp.971-980
• /
• 2010

In this paper, we present a navigation control algorithm for mobile robots that move in environments having static and moving obstacles. The algorithm includes a global and a local path-planning algorithm that uses $D^*$ search algorithm, a fuzzy logic for determining the immediate level of danger due to collision, and a fuzzy logic for evaluating the required wheel velocities of the mobile robot. To apply the $D^*$ search algorithm, the two-dimensional space that the robot moves in is decomposed into small rectangular cells. The algorithm is verified by performing simulations using the Python programming language as well as by using the dynamic equations for a two-wheeled mobile robot. The simulation results show that the algorithm can be used to move the robot successfully to reach the goal position, while avoiding moving and unknown static obstacles.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.2
• /
• pp.169-178
• /
• 1997

This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept, avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of three state variables: the distance from the obstacle to the robot, outward speed of the obstacle relative to the robot, and outward speed of the robot relative to the obstacle. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid a moving obstacle in real time. Since the algorithm considers the mobility of the obstacle and robot as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.9
• /
• pp.716-722
• /
• 2016

Coordinate estimation is an essential function for autonomous navigation of a mobile robot. The optical mouse sensor is convenient and cost-effective for the coordinate estimation problem. It is possible to overcome the position estimation error caused by the slip and the model mismatch of robot's motion equation using the optical mouse sensor. One of the simple methods for the position estimation using the optical mouse sensor is integration of the velocity data from the sensor with time. However, the unavoidable noise in the sensor data may deteriorate the position estimation in case of the simple integration method. In general, a mobile robot has ready-to-use motion information from the encoder sensors of driving motors. By combining the velocity data from the optical mouse sensor and the motion information of a mobile robot, it is possible to improve the coordinate estimation performance. In this paper, a coordinate estimation algorithm for an autonomous mobile robot is presented based on the well-known Kalman filter that is useful to combine the different types of sensors. Computer simulation results show the performance of the proposed localization algorithm for several types of trajectories in comparison with the simple integration method.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.620-622
• /
• 2004

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and the floor decreases suddenly, the robot has a slip state. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weigh. Secondly, reposed fuzzy logic applied by the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takaki-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. In additionally, this algorithm controls recovered driving torque for the restrain the re-slip. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena through that compare fuzzy with PI control for the controller performance in the re-adhesion control strategy. These procedures are implemented using a Pioneer 2-DXE wheeled robot parameter.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.2
• /
• pp.16-28
• /
• 2000

In this paper, we propose a navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using an ultrasonic sensor. Instead of using "sensor fusion"method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion"method is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we peformed simulations in PC as well as real experiments with ZIRO. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.