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Events for May 25, 2017

  • PhD Defense - Luenin Barrios

    Thu, May 25, 2017 @ 10:00 AM - 12:00 PM

    Computer Science

    University Calendar

    PhD Candidate: Luenin Barrios

    Committee: Wei-Min Shen (chair), Stephan Haas, Aiichiro Nakano.

    Title: Simultaneous Center of Mass Estimation and Foot Placement Selection in Complex Planar Terrains for Legged Architectures

    Time: Thursday, May 25 at 10am

    Room: SAL 213

    Center of Mass (CoM) path planning and foot placement selection in complex and rough terrains remains an important goal in the development of motion plans for legged robots. Precise CoM measurements and percipient foot placements are essential in understanding the behavior of a system, for example in gait selection or in extreme locomotion maneuvers. However, operating and maneuvering in difficult terrains has remained a challenging problem due to the diversity of environments and the complex interplay of foot placements and CoM motions. These locomotion maneuvers involve complex forces and movements that make analysis of CoM behavior a challenging task. Nevertheless, understanding CoM dynamics remains pivotal in locomotion planning for both humans and robots. Indeed, the critical element in robot and human motion planning revolves around the ability to accurately measure and describe the CoM. But given the cyclopean space of natural terrains available and the large number of kinematic shapes and sizes possible, the question arises: Is it conceivable to create a generalized framework for CoM construction and estimation with optimal foot placement selection that incorporates the large variety of kinematic architectures and terrains? The work described in this research addresses this issue by presenting a generalized geometric framework from which accurate CoM estimates are produced for the case of bipedal locomotion in complex planar terrains. This framework allows for the simultaneous treatment of CoM estimation and foot placement selection in legged architectures in an efficient and straightforward manner. This is a marked change from current methods for CoM position estimation that rely heavily on expensive and ungainly tools, for example force plates and motion capture video. These render CoM analysis impractical and time consuming and serve as an impediment to understanding locomotion maneuvers in uneven terrains. To tackle these challenges, this work proposes a reliable geometric approach for CoM estimation that delivers accurate CoM behavior in complex planar terrains. The geometric approach depends only on terrain geometry information and essential kinematic data of the moving body. Using this key information in conjunction with an Optimized Geometric Hermite (OGH) curve, a model is developed that produces accurate CoM position and phase space behavior. This phase space behavior is simultaneously optimized during CoM estimation to find candidate foot locations that produce an overall plan with minimum energy. This provides a way to synthesize complex maneuvers in rough terrains and to develop accurate CoM estimates and foot placement plans. Various human case studies were analyzed to validate the effectiveness of the approach. The results show that for natural walking over complex planar terrains, the geometric approach generates accurate CoM path approximations and state space trajectories and is a powerful tool for understanding CoM behavior and foot placements in irregular planar terrains.

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon