Browsing by Subject "Trajectories"

Now showing 1 - 6 of 6

Open Access
Approximate analytic solutions to non-symmetric stance trajectories of the passive Spring-Loaded Inverted Pendulum with damping
(Springer Netherlands, 2010) Saranlı U.; Arslan, Ö.; Ankaralı, M. M.; Morgül, Ö.
This paper introduces an accurate yet analytically simple approximation to the stance dynamics of the Spring-Loaded Inverted Pendulum (SLIP) model in the presence of non-negligible damping and non-symmetric stance trajectories. Since the SLIP model has long been established as an accurate descriptive model for running behaviors, its careful analysis is instrumental in the design of successful locomotion controllers. Unfortunately, none of the existing analytic methods in the literature explicitly take damping into account, resulting in degraded predictive accuracy when they are used for dissipative runners. We show that the methods we propose not only yield average predictive errors below 2% in the presence of significant damping, but also outperform existing alternatives to approximate the trajectories of a lossless model. Finally, we exploit both the predictive performance and analytic simplicity of our approximations in the design of a gait-level running controller, demonstrating their practical utility and performance benefits. © 2010 Springer Science+Business Media B.V.
Open Access
An approximate stance map of the spring mass hopper with gravity correction for nonsymmetric locomotions
(IEEE, 2009) Arslan, Ömür; Saranlı, Uluç; Morgül, Ömer
The Spring-Loaded Inverted Pendulum (SLIP) model has long been established as an effective and accurate descriptive model for running animals of widely differing sizes and morphologies, while also serving as a basis for several hopping robot designs. Further research on this model led to the discovery of several analytic approximations to its normally nonintegrable dynamics. However, these approximations mostly focus on steady-state running with symmetric trajectories due to their linearization of gravitational effects, an assumption that is quickly violated for locomotion on more complex terrain wherein transient, non-symmetric trajectories dominate. In this paper, we introduce a novel gravity correction scheme that extends on one of the more recent analytic approximations to the SLIP dynamics and achieves good accuracy even for highly non-symmetric trajectories. Our approach is based on incorporating the total effect of gravity on the angular momentum throughout a single stance phase and allows us to preserve the analytic simplicity of the approximation to support our longer term research on reactive footstep planning for dynamic legged locomotion. We compare the performance of our method in simulation to two other existing analytic approximations and show that it outperforms them for most physically realistic non-symmetric SLIP trajectories while maintaining the same accuracy for symmetric trajectories. © 2009 IEEE.
Open Access
A hand gesture recognition technique for human-computer interaction
(Academic Press, 2015) Kılıboz, N. Ç.; Güdükbay, Uğur
We propose an approach to recognize trajectory-based dynamic hand gestures in real time for human-computer interaction (HCI). We also introduce a fast learning mechanism that does not require extensive training data to teach gestures to the system. We use a six-degrees-of-freedom position tracker to collect trajectory data and represent gestures as an ordered sequence of directional movements in 2D. In the learning phase, sample gesture data is filtered and processed to create gesture recognizers, which are basically finite-state machine sequence recognizers. We achieve online gesture recognition by these recognizers without needing to specify gesture start and end positions. The results of the conducted user study show that the proposed method is very promising in terms of gesture detection and recognition performance (73% accuracy) in a stream of motion. Additionally, the assessment of the user attitude survey denotes that the gestural interface is very useful and satisfactory. One of the novel parts of the proposed approach is that it gives users the freedom to create gesture commands according to their preferences for selected tasks. Thus, the presented gesture recognition approach makes the HCI process more intuitive and user specific.
Open Access
Numerical analysis of mixing performance in sinusoidal microchannels based on particle motion in droplets
(Springer Verlag, 2015) Özkan, A.; Erdem, E. Y.
This numerical study was conducted to analyze and understand the parameters that affect the mixing performance of droplet-based flow in sinusoidal microfluidic channels. Finite element analysis was used for modeling fluid flow and droplet formation inside the microchannels via tracking interface between the two heterogeneous fluids along with multiple particle trajectories inside a droplet. The solutions of multiphase fluid flow and particle trajectories were coupled with each other so that drag on every single particle changed in every time step. To solve fluid motion in multiphase flow, level set method was used. Parametric study was repeated for different channel dimensions and different sinusoidal channel profiles. These results were compared with mixing in droplets inside a straight microchannel. Additionally, tracking of multiple particles inside a droplet was performed to simulate the circulating flow profile inside the droplets. Based on the calculation of the dispersion length, particle trajectories, and velocities inside droplets, it is concluded that having smaller channel geometries increases the mixing performance inside the droplet. This also shows that droplet-based fluid flow in microchannels is very suitable for performing chemical reactions inside droplets as it will occur faster. Moreover, narrower and sinusoidal microchannels showed better dispersion length difference compared to straight and wider microchannels.
Open Access
Snippet based trajectory statistics histograms for assistive technologies
(Springer, 2014-09) İscen, Ahmet; Wang Y.; Duygulu, Pınar; Hauptmann, A.
Due to increasing hospital costs and traveling time, more and more patients decide to use medical devices at home without traveling to the hospital. However, these devices are not always very straight-forward for usage, and the recent reports show that there are many injuries and even deaths caused by the wrong use of these devices. Since human supervision during every usage is impractical, there is a need for computer vision systems that would recognize actions and detect if the patient has done something wrong. In this paper, we propose to use Snippet Based Trajectory Statistics Histograms descriptor to recognize actions in two medical device usage problems; inhaler device usage and infusion pump usage. Snippet Based Trajectory Statistics Histograms encodes the motion and position statistics of densely extracted trajectories from a video. Our experiments show that by using Snippet Based Trajectory Statistics Histograms technique, we improve the overall performance for both tasks. Additionally, this method does not require heavy computation, and is suitable for real-time systems. © Springer International Publishing Switzerland 2015.
Open Access
What is usual in unusual videos? trajectory snippet histograms for discovering unusualness
(IEEE, 2014-06) İşcen, Ahmet; Armağan, Anıl; Duygulu, Pınar
Unusual events are important as being possible indicators of undesired consequences. Moreover, unusualness in everyday life activities may also be amusing to watch as proven by the popularity of such videos shared in social media. Discovery of unusual events in videos is generally attacked as a problem of finding usual patterns, and then separating the ones that do not resemble them. In this study, we address the problem from a different perspective, and try to answer what type of patterns are shared among unusual videos that make them resemble to each other regardless of the ongoing event. With this challenging problem at hand, we propose a novel descriptor to encode the rapid motions in videos utilizing densely extracted trajectories. The proposed descriptor, which is referred to as trajectory snipped histograms, is used to distinguish unusual videos from usual videos, and further exploited to discover snapshots in which unusualness happen. Experiments on domain specific people falling videos and unrestricted funny videos show the effectiveness of our method in capturing unusualness. © 2014 IEEE.