WSPC- Proceedings Trim Size: 9in x 6in main 1 Characterizing Swing-Leg Retraction in Human Locomotion

contact, is observed in human locomotion. While several advantages of swingleg retraction, like gait stability and perturbation rejection, are shown by conceptual models, there is currently very little experimental data on swing-leg retraction in human motion. In this paper, kinematic data for twenty-eight subjects walking and running at different speeds are analyzed. Swing-leg retraction was shown to exist in walking and running at every non-zero speed. Additionally, swing-leg retraction speed and acceleration linearly increase with gait speed. At comparable gait speeds, swing-leg retraction speed is higher for running than for walking

The effect of swing leg retraction on biped walking stability is influenced by the walking speed and step-length

Swing Leg Retraction (SLR) is observed in human walking and running. Previous studies have concluded that SLR improves the stability and robustness of biped walking. But this conclusion was based on analysis of robot models that can only walk at a very small range of step-lengths and slow or fixed speeds. By contrast, humans can walk with a large range of speeds and step-lengths. Moreover, human walking patterns have a special feature that has not been considered in the previous studies on SLR effects: At a given walking speed, v, humans prefer a step-length, s, which satisfies the power law, s-v β . Therefore, previous studies on SLR can't tell us whether their conclusion will still hold in the full range of human walking patterns (i.e., various walking speeds and step-lengths). This is the question we want to answer in this paper. In this study, using a simple biped model, we studied how the SLR affects the walking stability in the full range of human walking speeds/step-lengths. Preliminary analysis of both models suggests the same conclusion: (1) SLR improves the stability more evidently in human-preferred walking patterns than in other walking patterns. (2) In walking patterns that are very unlike human-preferred ones, the SLR improves the stability very little, or even deteriorates it drastically. Therefore, the new finding of our study is that how the SLR affects the biped walking stability depends on the walking speed and step-length. SLR does not always improve the stability of biped walking

Design Development and Analysis of Humanoid Robot

Humanoid robots are those resembling their motion and functioning similar to human beings, having capabilities of doing day to day activities similar to man and replace him in every possible way. These activities vary from daily activities such as walking, standing, and bowing, to staircase climbing, running, and kneeling. The current research integrates multiple technologies and methodologies within a system such as 3D printing, Inverse Kinematic programming, Power electronics, Control system, Learning algorithms, Mechanical Design, Human-computer interaction, software tools for collaborative projects. A detailed mechanical design procedure has been carried out in CAD along with its structural analysis in FEA. Followed by Kinematic and Dynamic analysis of the system considering suitable physical properties in V-re

The effect of swing leg retraction on biped walking stability is influenced by the walking speed and step-length

Swing Leg Retraction (SLR) is observed in human walking and running. Previous studies have concluded that SLR improves the stability and robustness of biped walking. But this conclusion was based on analysis of robot models that can only walk at a very small range of step-lengths and slow or fixed speeds. By contrast, humans can walk with a large range of speeds and step-lengths. Moreover, human walking patterns have a special feature that has not been considered in the previous studies on SLR effects: At a given walking speed, v, humans prefer a step-length, s, which satisfies the power law, s-v β . Therefore, previous studies on SLR can't tell us whether their conclusion will still hold in the full range of human walking patterns (i.e., various walking speeds and step-lengths). This is the question we want to answer in this paper. In this study, using a simple biped model, we studied how the SLR affects the walking stability in the full range of human walking speeds/step-lengths. Preliminary analysis of both models suggests the same conclusion: (1) SLR improves the stability more evidently in human-preferred walking patterns than in other walking patterns. (2) In walking patterns that are very unlike human-preferred ones, the SLR improves the stability very little, or even deteriorates it drastically. Therefore, the new finding of our study is that how the SLR affects the biped walking stability depends on the walking speed and step-length. SLR does not always improve the stability of biped walking

Fractal mechanism of basin of attraction in passive dynamic walking

Passive dynamic walking is a model that walks down a shallow slope without any control or input. This model has been widely used to investigate how humans walk with low energy consumption and provides design principles for energy-efficient biped robots. However, the basin of attraction is very small and thin and has a fractal-like complicated shape, which makes producing stable walking difficult. In our previous study, we used the simplest walking model and investigated the fractal-like basin of attraction based on dynamical systems theory by focusing on the hybrid dynamics of the model composed of the continuous dynamics with saddle hyperbolicity and the discontinuous dynamics caused by the impact upon foot contact. We clarified that the fractal-like basin of attraction is generated through iterative stretching and bending deformations of the domain of the Poincaré map by sequential inverse images. However, whether the fractal-like basin of attraction is actually fractal, i.e., whether infinitely many self-similar patterns are embedded in the basin of attraction, is dependent on the slope angle, and the mechanism remains unclear. In the present study, we improved our previous analysis in order to clarify this mechanism. In particular, we newly focused on the range of the Poincaré map and specified the regions that are stretched and bent by the sequential inverse images of the Poincaré map. Through the analysis of the specified regions, we clarified the conditions and mechanism required for the basin of attraction to be fractal

Minimalistic control of biped walking in rough terrain

Toward our comprehensive understanding of legged locomotion in animals and machines, the compass gait model has been intensively studied for a systematic investigation of complex biped locomotion dynamics. While most of the previous studies focused only on the locomotion on flat surfaces, in this article, we tackle with the problem of bipedal locomotion in rough terrains by using a minimalistic control architecture for the compass gait walking model. This controller utilizes an open-loop sinusoidal oscillation of hip motor, which induces basic walking stability without sensory feedback. A set of simulation analyses show that the underlying mechanism lies in the “phase locking” mechanism that compensates phase delays between mechanical dynamics and the open-loop motor oscillation resulting in a relatively large basin of attraction in dynamic bipedal walking. By exploiting this mechanism, we also explain how the basin of attraction can be controlled by manipulating the parameters of oscillator not only on a flat terrain but also in various inclined slopes. Based on the simulation analysis, the proposed controller is implemented in a real-world robotic platform to confirm the plausibility of the approach. In addition, by using these basic principles of self-stability and gait variability, we demonstrate how the proposed controller can be extended with a simple sensory feedback such that the robot is able to control gait patterns autonomously for traversing a rough terrain.National Science Foundation (U.S.) (grant 0746194)Swiss National Science Foundation (grant PBZH2-114461)Swiss National Science Foundation (grant PP00P2_123387/1