A landslide located on the Quesnel River in British Columbia, Canada is used as a case study to demonstrate the utility of a multi-geophysical approach to subsurface mapping of unstable slopes. Ground penetrating radar (GPR), direct current (DC) resistivity and seismic reflection and refraction surveys were conducted over the landslide and adjacent terrain. Geophysical data were interpreted based on stratigraphic and geomorphologic observations, including the use of digital terrain models (DTMs), and then integrated into a 3-dimensional model. GPR surveys yielded high-resolution data that were correlated with stratigraphic units to a maximum depth of 25 m. DC electrical resistivity offered limited data on specific units but was effective for resolving stratigraphic relationships between units to a maximum depth of 40 m. Seismic surveys were primarily used to obtain unit boundaries up to a depth of >80 m. Surfaces of rupture and separation were successfully identified by GPR and DC electrical resistivity techniques.
This paper presents a hybrid approach to the animation of human locomotion which combines goal-directed and dynamic motion control. Knowledge about a locomotion cycle is incorporated into a hierarchical control process. The desired locomotion is conveniently specified at the top level as a task (e.g. walk at speed
v
), which is then decomposed by application of the concepts of
step symmetry
and
state-phase-timings
. As a result of this decomposition, the forces and torques that drive the dynamic model of the legs are determined by numerical approximation techniques. Rather than relying on a general dynamic model, the equations of motion of the legs are tailored to locomotion and analytically constrained to allow for only a specific range of movements. The dynamics of the legs produce a generic, natural locomotion pattern which is visually upgraded by some kinematic "cosmetics" derived from such principles as
virtual leg
and
determinants of gait
. A system has been implemented based on these principles and has shown that when a few parameters, such as velocity, step length and step frequency are specified, a wide variety of human walks can be generated in almost real-time.
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