• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.4
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• pp.199-206
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• 2006

Real time vehicle dynamics models have been developed with the subsystem synthesis method for intelligent vehicle HILS system. Three different models for solving subsystem equations are compared in order to find out the best suitable model for HILS applications. The first model is based on the generalized coordinate partitioning technique, and the second one is on the approximate function approach, and the last one is on the constraint stabilization method. To investigate the theoretical efficiency of three proposed methods, arithmetic operators used in the formulations of three models are counted. Bump run simulations with half-sine bump have also carried out with three different models to measure the actual CPU time to validate theoretical investigation.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.113-121
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• 2020

Human Pose Estimation (HPE) which localizes the human body joints becomes a high potential for high-level applications in the field of computer vision. The main challenges of HPE in real-time are occlusion, illumination change and diversity of pose appearance. The single RGB image is fed into HPE framework in order to reduce the computation cost by using depth-independent device such as a common camera, webcam, or phone cam. However, HPE based on the single RGB is not able to solve the above challenges due to inherent characteristics of color or texture. On the other hand, depth information which is fed into HPE framework and detects the human body parts in 3D coordinates can be usefully used to solve the above challenges. However, the depth information-based HPE requires the depth-dependent device which has space constraint and is cost consuming. Especially, the result of depth information-based HPE is less reliable due to the requirement of pose initialization and less stabilization of frame tracking. Therefore, this paper proposes a new method of HPE which is robust in estimating self-occlusion. There are many human parts which can be occluded by other body parts. However, this paper focuses only on head self-occlusion. The new method is a combination of the RGB image-based HPE framework and the depth information-based HPE framework. We evaluated the performance of the proposed method by COCO Object Keypoint Similarity library. By taking an advantage of RGB image-based HPE method and depth information-based HPE method, our HPE method based on RGB-D achieved the mAP of 0.903 and mAR of 0.938. It proved that our method outperforms the RGB-based HPE and the depth-based HPE.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1069-1075
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• 2013

An effective method is necessary for the real-time analysis of an unmanned military robot. To achieve highly efficient simulations, a subsystem synthesis method has been developed. The subsystem synthesis method separately generates equations of motion for the base body and for the subsystem. The equations of motion are expressed by DAE, which consist of differential equations and algebraic equations. To increase the accuracy and efficiency of solutions, DAE solvers such as the Direct, CS (Constraint Stabilization), and GCP (Generalized Coordinate Partitioning) method are employed. In this study, the subsystem synthesis method is applied for effective multi-body dynamics analysis of an unmanned military robot, and a comparative study of three different DAE solvers is carried out.