• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.831-836
• /
• 2007

This paper proposes an optimal galloping trajectory which costs low energy and guarantees the stability of the quadruped robot. In the realization of the fast galloping, the trajectory design is important. As a galloping trajectory, we propose an elliptic leg trajectory, which provides simplified locomotion to complex galloping motions of animals. However, the elliptic trajectory, as an imitation of animal galloping motion, does not guarantee stability and minimal energy consumption. We propose optimization based on the energy and stability using a genetic algorithm, which provides the robust and global solution to a multi-body, highly nonlinear dynamic system. To evaluate and verify the effectiveness of the proposed trajectory, computer simulations were carried out.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.11
• /
• pp.91-99
• /
• 2003

When the driver suddenly depresses the brake pedal under critical conditions, the desired trajectory of the vehicle can be changed. In this study, the vehicle dynamics and fuzzy logic controller are used to control the vehicle trajectory. The dynamic vehicle model consists of the engine, the rotational wheel, chassis, tires and brakes. The engine model is derived from the engine experimental data. The engine torque makes the wheel rotate and generates the angular velocity and acceleration of the wheel. The dynamic equation of the vehicle model is derived from the top-view vehicle model using Newton's second law. The Pacejka tire model formulated from the experimental data is used. The fuzzy logic controller is developed to compensate for the trajectory error of the vehicle. This fuzzy logic controller individually acts on the front right, front left, rear right and rear left brakes and regulates each brake torque. The fuzzy logic controlling each brake works to compensate for the trajectory error on the split - $\mu$ road conditions follows the desired trajectory.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.10
• /
• pp.997-1005
• /
• 2010

Most motion control systems consist of a desired trajectory generator, a motion controller such as a conventional PID controller, and a plant to be controlled. The desired trajectory generator as well as the motion controller is very important to achieve a good tracking performance. Especially, if the desired trajectory is generated actively utilizing the maximum velocity, acceleration, jerk and snap as given system specifications, the tracking performance would be better. For this, we make use of the properties of convolution operator in order to generate a smooth (S-curve) trajectory satisfying the system specifications. Also, the proposed trajectory generation method is extended to more general cases with arbitrary initial and terminal conditions. In addition, the suggested trajectory generator can be easily realized for real-time implementation. Finally, the effectiveness of the suggested method is shown through numerical simulations.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.9
• /
• pp.845-853
• /
• 2012

We propose time-optimal cornering motion trajectory planning and control algorithms for differential wheeled mobile robot with motor actuating voltage constraint, under piecewise constant control input condition. For time-optimal cornering trajectory generation, 1) we considered mobile robot's dynamics including actuator motors, 2) divided the cornering trajectory into one liner section, followed by two cornering section with angular acceleration and deceleration, and finally one liner section, and 3) formulated an efficient trajectory generation algorithm satisfying the bang-bang control principle. Also we proposed an efficient trajectory control algorithm and implemented with an X-bot to prove the performance.

• Journal of Positioning, Navigation, and Timing
• /
• v.12 no.4
• /
• pp.409-421
• /
• 2023

In order to develop navigation systems, simulators that provide navigation sensors data are required. A trajectory generator that simulates vehicle motion is needed to generate navigation sensors data in the simulator. In this paper, a trajectory generator for evaluating navigation system performance is proposed. The proposed trajectory generator consists of two parts. The first part obtains parameters from the motion scenario file whereas the second part generates position, velocity, and attitude from the parameters. In the proposed trajectory generator six degrees of freedom, halt, climb, turn, accel turn, spiral, combined, and waypoint motions are given as basic motions with parameters. These motions can be combined to generate complex trajectories of the vehicle. Maximum acceleration and jerk for linear motion and maximum angular acceleration and velocity for rotational motion are considered to generate trajectories. In order to show the usefulness of the proposed trajectory generator, trajectories were generated from motion scenario files and the results were observed. The results show that the proposed trajectory generator can accurately simulate complex vehicle motions that can be used to evaluate navigation system performance.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.3
• /
• pp.145-153
• /
• 2009

Trajectory data are ubiquitous in the real world. Recent progress on satellite, sensor, RFID, video, and wireless technologies has made it possible to systematically track object movements and collect huge amounts of trajectory data. Accordingly, there is an ever-increasing interest in performing data analysis over trajectory data. In this paper, we develop a data mining tool for massive trajectory data. This mining tool supports three operations, clustering, classification, and outlier detection, which are the most widely used ones. Trajectory clustering discovers common movement patterns, trajectory classification predicts the class labels of moving objects based on their trajectories, and trajectory outlier detection finds trajectories that are grossly different from or inconsistent with the remaining set of trajectories. The primary advantage of the mining tool is to take advantage of the information of partial trajectories in the process of data mining. The effectiveness of the mining tool is shown using various real trajectory data sets. We believe that we have provided practical software for trajectory data mining which can be used in many real applications.

• The Journal of Korea Robotics Society
• /
• v.6 no.4
• /
• pp.301-307
• /
• 2011

Based on the stability criteria of ZMP (Zero Moment Point), this paper proposes an adjusting algorithm that modifies walking trajectory of a bipedal robot for stable walking by analyzing ZMP trajectory of it. In order to maintain walking balance of the bipedal robot, ZMP should be located within a supporting polygon that is determined by the foot supporting area with stability margin. Initially tilting imposed to the trajectory of the upper body is proposed to transfer ZMP of the given walking trajectory into the stable region for the minimum stability. A neural network method is also proposed for the stable walking trajectory of the biped robot. It uses backpropagation learning with angles and angular velocities of all joints with tilting to get the improved walking trajectory. By applying the optimized walking trajectory that is obtained with the neural network model, the ZMP trajectory of the bipedal robot is certainly located within a stable area of the supporting polygon. Experimental results show that the optimally learned trajectory with neural network gives more stability even though the tilting of the pelvic joint has a great role for walking stability.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.1
• /
• pp.68-75
• /
• 2003

This paper presents an effective trajectory planning algorithm for industrial robot manipulators. Given the end-effector trajectory in Cartesian space, together with the relevant constraints and task specifications, the proposed method is capable of planning the optimum end-effector trajectory. The proposed trajectory planning algorithm considers the joint acceleration limit, end-effector velocity limits, and trajectory allowance. A feedforward compensator is also incorporated in the proposed algorithm to counteract the delay in joint dynamics. The algorithm is carefully designed so that it can be directly adopted with the existing industrial manipulators. The proposed algorithm can be easily programmed for various tasks given the specifications and constraints. A three-dimensional test trajectory was planned with the proposed algorithm and tested with the Performer MK3s industrial manipulator. The results verified effective manipulator performance within the constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.2
• /
• pp.600-619
• /
• 2015

We propose a cost-efficient hybrid algorithm for online location updates that efficiently combines feature point detection with the online trajectory-based sampling algorithm. Our algorithm is designed to minimize the average trajectory error with the minimal number of sample points. The algorithm is composed of 3 steps. First, we choose corner points from the map as sample points because they will most likely cause fewer trajectory errors. By employing the online trajectory sampling algorithm as the second step, our algorithm detects several missing and important sample points to prevent unwanted trajectory errors. The final step improves cost efficiency by eliminating redundant sample points on straight paths. We evaluate the proposed algorithm with real GPS trajectory data for various bus routes and compare our algorithm with the existing one. Simulation results show that our algorithm decreases the average trajectory error 28% compared to the existing one. In terms of cost efficiency, simulation results show that our algorithm is 29% more cost efficient than the existing one with real GPS trajectory data.

• Korean Journal of Health Education and Promotion
• /
• v.34 no.1
• /
• pp.25-34
• /
• 2017

Objectives: Although the number of the oldest-old is rapidly increasing due to longevity, very little is known about the trajectory of depressive symptoms(DS) and its related factors among the oldest-old. Much less is known about whether the trajectory of DS differs by gender among the oldest-old. The current study aims (1) to estimate the trajectory of DS and (2) to examine whether the trajectory differs by gender among the oldest-old. Methods: Sample consists of 296 persons aged 85 and over who participated in the Korean Welfare Panel Study data. Data were processed using the latent growth curve modeling to estimate the trajectory and multi-group SEM to examine gender difference. Results: This study showed that (1) the trajectory of DS was increasing over time and (2) the DS trajectory of males was much more rapidly increasing than that of females, indicating male oldest old are more vulnerable to depression than female oldest old in later life. Conclusions: Given the fact that females are known to be more vulnerable to depression, the findings are counterintuitive to the previous knowledge on depression and gender difference. Based on the findings, implications for intervention and education related to DS among the oldest-old.