• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1145-1151
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• 2013

Kinematic modeling is a prerequisite for motion planning and the control of mobile robots. In this paper, we proposed a new method of kinematic modeling for a type of mobile robot based on differential motion transformation. The differential motion implies a small translation and rotation in three-dimensional space in a small time interval. Thus, transformation of the differential motion gives the velocity relationship, i.e., Jacobian between two coordinate frames. Since the theory of the differential motion transformation is well-developed, it is useful for the systematic velocity kinematic modeling of mobile robots. In order to show the validity for application of the differential motion transformation, we obtained velocity kinematic models for a type of exemplar mobile robot including spherical ballbots.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.1
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• pp.28-36
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• 2002

Regarding efficient development of computer graphic animations, lots of techniques for editing or transforming existing motion data have been developed. Basically, the motion transformation techniques follow optimization process. To make the animation be natural, almost all the techniques utilize kinematics and dynamics in constructing constraints for the optimization. Since the kinematic and dynamic structures of virtual characters to be animated are very complex, the most time-consuming part is known to the optimization process. In order to suggest some guide lines to engineers involved in the motion transformation, in this paper, we analyze the computational complexities for typical motion transformation in quantitative manner as well as the possibility for parallel computation.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.292-297
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• 2013

This paper presents a new method of kinematic modeling for autonomous bicycle by using the differential motion transformation. Kinematic model is indispensable to trajectory planning and control for an autonomous mobile robot. The conventional methods of kinematic modeling for an autonomous bicycle depend on intuition by geometry. On the contrary, the proposed method in this paper is based on the systematic differential motion transformation, thus applicable to various types of autonomous bicycles. The differential motion transformation gives Jacobian between two coordinate frames and the velocity kinematics as a result.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.167-178
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• 2001

This paper presents a new methodology for specification and control of the motion of an articulated rigid body for the purposes of animation by coordinate transformations. The approach is to formulate the problem as a coordinate transformation from the joint space of the body to a user-defined animation space which is chosen for convenience in constraining the motion. Constraints are applied to the resulting coordinate transformation equations. It is sufficiently general so that it can be applied to all common types of control problems, including closed loop as well as open loop mechanisms. We also provided a new approach to simulate a closed loop mechanism, which is using animation space transformation technique. The method is formulated in detail and is demonstrated by animating the motion of an inchworm.

• Journal of Sensor Science and Technology
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• v.28 no.1
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• pp.30-35
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• 2019

Inertial measurement units (IMUs) are widely used for wearable motion-capturing systems in the fields of biomechanics and robotics. When the IMUs are combined with optical motion sensors (hereafter, OPTs) for their complementary capabilities, it is necessary to align the coordinate system orientations between the IMU and OPT. In this study, we compare the application of two coordinate transformation-based orientation alignment methods between two coordinate systems. The first method (M1) applies angular velocity coordinate transformation, while the other method (M2) applies gyroscopic angle coordinate transformation. In M1 and M2, the angular velocities and angles, respectively, are acquired during random movement for a least-square algorithm to determine the alignment matrix between the two coordinate systems. The performance of each method is evaluated under various conditions according to the type of motion during measurement, number of data points, amount of noise, and the alignment matrix. The results show that M1 is free from drift errors, while drift errors are present in most cases where M2 is applied. Thus, this study indicates that M1 has a far superior performance than M2 for the alignment of IMU and OPT coordinate systems for motion analysis.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.488-494
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• 2001

Many literatures, so far, have concentrated on approaches employing dependent coordinates set resulting in computational burden of constraint forces, which is needless in many cases. Some researchers developed methods to remove or calculate it efficiently. But systematic generation of the motion equation using independent coordinates set by Kane's equation is possible for any closed loop system. Independent velocity transformation method builds the smallest size of motion equation, but needs practically more complicated code implementation. In this study, dependent velocity matrix is systematically transformed into independent one using dependent-independent transformation matrix of each body group, and then motion equation free of constraint force is constructed. This method is compared with the other approach by counting the number of multiplications for car model with 15 d.o.f..

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.370-376
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• 2023

Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1671-1674
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• 1997

In tihs paper, an acceleratiion transformation algorithm which compensates the sculling error is proposed for strapdown inertial navigation system. The algorithm utilize the corss-product of the acceleromenter outputs and gyro outputs to keep the accuracy of the vehicle velocity under high frequency dynamic motion. From the error analysis of the algorithm, it is shown that the magnitude of estimation error is reduced by four orders.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.21-27
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• 2015

A conventional fire detection has been developed based on images captured from a fixed camera. However, It is difficult to apply current algorithms to a flying Quad-rotor to detect fire. To solve this problem, we propose that the fire detection algorithm can be modified for Quad-rotor using Ego-motion compensation. The proposed fire detection algorithm consists of color detection, motion detection, and fire determination using a randomness test. Color detection and randomness test are adapted similarly from an existing algorithm. However, Ego-motion compensation is adapted on motion detection for compensating the degree of Quad-rotor's motion using Planar Projective Transformation based on Optical Flow, RANSAC Algorithm, and Homography. By adapting Ego-motion compensation on the motion detection step, it has been proven that the proposed algorithm has been able to detect fires 83% of the time in hovering mode.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.1
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• pp.101-111
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• 2001

Recursive formulas have been effective in solving the equations of motion for large scale constratined mechanical sys-tems. However, derivation of the formulas has been limited to individual terms in the equations of motion, such as veloci-ty, acceleration. and generalized forces. The recursive formulas are generalized in this paper. The velocity transformation method is employed to transform the equations of motion from Cartesian to the joint spaces. Computational structure of the equations of motion in the joint space is carefully examined to classify all necessary computational operations into sev-eral categories. The generalized recursive formula for each category is then developed and applied whenever such a cate-gory of computation is encountered. Since the velocity transformation method yields the equations of motion in a compact form and computational efficiency is achieved by generalized recursive formulas, the proposed method is not only easy to implement but is also efficient. A library of generalized recursive formulas is developed to implement a dynamic analysis algorithm using backward difference.