Choon-Young Lee

Collision Avoidance by the Fusion of Different Beam-width Ultrasonic Sensors

So far, mobile robot equipped with multiple ultrasonic sensors with fixed beam-width has been used in robot navigation. In this paper, we used multiple ultrasonic sensors with different beam-widths in mobile robot navigation. The use of ultrasonic sensor with small beam-width gives good resolution in recognizing environmental condition and we need more sensors to detect obstacles in wide angular region. However, if we use wide beam-width ultrasonic sensors, we can detect surrounding obstacles with a few sensors. By fusing the aspects of ultrasonic sensors with different beam-widths, we can obtain more efficient collision avoidance behavior in robot control. We stacked three kinds of ultrasonic sensors and get distance information from each sensor. Small beam-width sensor can detect environment with high resolution and large beam-width sensor gives information on possible obstacles in robot motion. Using the approach, the robot can navigate through a complex environment.

New separation algorithm for touching grain kernels based on contour segments and ellipse fitting

A new separation algorithm based on contour segments and ellipse fitting is proposed to separate the ellipse-like touching grain kernels in digital images. The image is filtered and converted into a binary image first. Then the contour of touching grain kernels is extracted and divided into contour segments (CS) with the concave points on it. The next step is to merge the contour segments, which is the main contribution of this work. The distance measurement (DM) and deviation error measurement (DEM) are proposed to test whether the contour segments pertain to the same kernel or not. If they pass the measurement and judgment, they are merged as a new segment. Finally with these newly merged contour segments, the ellipses are fitted as the representative ellipses for touching kernels. To verify the proposed algorithm, six different kinds of Korean grains were tested. Experimental results showed that the proposed method is efficient and accurate for the separation of the touching grain kernels.

Sonar sensor data processing based on optical flow in robot navigation

The application of optical flow techniques on artificial image sequences in computing relative motions of obstacles is studied as a data processing algorithm for ultrasonic sensors. These sensors in robot systems are widely used in calculating the distance of obstacles. However, owing to the angular uncertainty of sensor characteristics, limitations exist on the positioning of an objects location, making it difficult to obtain accurate velocity information. Collision avoidance in dynamic environments requires information on relative motion, such as distance and velocity. In this paper, a technique for image processing on a range of ultrasonic sensor data is suggested in order to obtain the relative motion of front objects. The proposed technique is conducted using a two-wheel differential drive robot for problem cases related to indoor navigation. Digital filtering is also conducted to smooth the fluctuations, after which relative velocity is calculated using the optical flow technique. Experimental results demonstrate the possible application of the proposed algorithm for robot navigation in dynamic environments. This technique will increase the intelligence of robot systems, allowing for effective sensing in various environmental conditions.

Application of RRT-based local Path Planning Algorithm in Unknown Environment

Path planning for mobile robots has received a great deal of attention over the past two decades. The basic rapidly-exploring random tree (RRT) algorithm is famous in this field because it excels at exploring free space in the large environments and it is parallelizable. In this paper, we applied modified RRT algorithm to local navigation of a mobile robot in unknown environment. The biased direction from RRT algorithm is used to reduce the nodes and therefore the amount of calculation is decreased for real-time computation. We conducted the simulation and simple real-time experiments to verify the proposed method in real unknown environment.

A Study on Particular Abnormal Gait Using Accelerometer and Gyro Sensor

Recently, technologies to help the elderly or disabled people who have difficulty in walking are being developed. In order to develop these technologies, it is necessary to construct a system that gathers the gait data of people and analysis of these data is also important. In this research, we constructed the development of sensor system which consists of pressure sensor, three-axis accelerometer and two-axis gyro sensor. We used k-means clustering algorithm to classify the data for characterization, and then calculated the symmetry index with histogram which was produced from each cluster. We collected gait data from sensors attached on two subjects. The experiment was conducted for two kinds of gait status. One is walking with normal gait; the other is walking with abnormal gait (abnormal gait means that the subject walks by dragging the right leg intentionally). With the result from the analysis of acceleration component, we were able to confirm that the analysis technique of this data could be used to determine gait symmetry. In addition, by adding gyro components in the analysis, we could find that the symmetry index was appropriate to express symmetry better.

Analysis on Kinematics and Dynamics of Human Arm Movement Toward Upper Limb Exoskeleton Robot Control Part 1: System Model and Kinematic Constraint

To achieve synchronized motion between a wearable robot and a human user, the redundancy must be resolved in the same manner by both systems. According to the seven DOF (Degrees of Freedom) human arm model composed of the shoulder, elbow, and wrist joints, positioning and orientating the wrist in space is a task requiring only six DOFs. Due to this redundancy, a given task can be completed by multiple arm configurations, and thus there exists no unique mathematical solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and their effect on the redundancy resolution of the human arm based on a seven DOF manipulator model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing different cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid for the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each two consecutive points along the task space trajectory. As a first step, the redundancy based on the kinematic criterion will be thoroughly studied based on the motion capture data analysis. Experimental results indicate that by using the proposed redundancy resolution criterion in the kinematic level, error between the predicted and the actual swivel angle acquired from the motor control system is less than five degrees.

Analysis on the Kinematics and Dynamics of Human Arm Movement Toward Upper Limb Exoskeleton Robot Control - Part 2: Combination of Kinematic and Dynamic Constraints

The redundancy resolution of the seven DOF (Degree of Freedom) upper limb exoskeleton is key to the synchronous motion between a robot and a human user. According to the seven DOF human arm model, positioning and orientating the wrist can be completed by multiple arm configurations that results in the non-unique solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and its effect on the redundancy resolution of the seven DOF human arm model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing two cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid of the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each of two consecutive points along the task space trajectory. The contribution of each criterion on the redundancy was verified by the post processing of experimental data collected with a motion capture system. Results indicate that the bimodal redundancy resolution approach improved the accuracy of the predicted swivel angle. Statistical testing of the dynamic constraint contribution shows that under moderate speeds and no load, the dynamic component of the human arm is not dominant, and it is enough to resolve the redundancy without dynamic constraint for the realtime application.

Recognition of Driving Patterns Using Accelerometers

In this paper, we proposed an algorithm to detect aggressive driving status by analysing six kinds of driving patterns, which was achieved by comparing for the feature vectors using mahalanobis distance. The first step is to construct feature matrix of size using frequency response of the time-series accelerometer data. Singular value decomposition makes it possible to find the dominant eigenvalue and its corresponding eigenvector. We use the eigenvector as the feature vector of the driving pattern. We conducted real experiments using three drivers to see the effects of recognition. Although there exists differences from individual drivers, we showed that driving patterns can be recognized with about 80% accuracy. Further research topics will include the development of aggressive driving warning system by improving the proposed technique and combining with post-processing of accelerometer signals.

Estimation of Inclination Angle of a Planar Reflector Using Sonar Sensor

A new processing technique of sonar echoes is introduced to estimate the inclination angle of a planar reflector. Correlation with normalized echo amplitude model and its derivatives has improved estimation accuracy. Experimental results show how a single transducer placed on a step motor can be used for estimating the reflectors orientation on a sensor coordinate system.

Recognition of Stance Phase for Walking Assistive Devices by Foot Pressure Patterns

In this paper, we proposed a technique to recognize three states in stance phase of gait cycle. Walking assistive devices are used to help the elderly people walk or to monitor walking behavior of the disabled persons. For the effective assistance, they adopt an intelligent sensor system to understand user`s current state in walking. There are three states in stance phase; Loading Response, Midstance, and Terminal Stance. We developed a foot pressure sensor using 24 FSRs (Force Sensing/Sensitive Resistors). The foot pressure patterns were integrated through the interpolation of FSR cell array. The pressure patterns were processed to get the trajectories of COM (Center of Mass). Using the trajectories of COM of foot pressure, we can recognize the three states of stance phase. The experimental results show the effective recognition of stance phase and the possibility of usage on the walking assistive device for better control and/or foot pressure monitoring.