Juan Rojas

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— Snap assembly automation remains a challenging task. While progress is being made in localization of parts, force controllers, and control strategies, little work has been done to help the robot reason about its current state, such that if necessary, the robot can assume corrective actions to accomplish the task. Error prone situations caused by the(More)
—Autonomous snap assemblies is a highly desirable robotic functionality. While much work has been done in active sensing for peg-in-hole assemblies and general compliant motions, snap assembly state estimation remains an open research problem. This work presents a probabilistic framework designed to account for uncertainties in assembly and yield more(More)
— In this work a gradient calibration method was presented as part of the Relative-Change-Based-Hierarchical Taxonomy (RCBHT) cantilever-snap verification system and the Pivot Approach control strategy for the automation of cantilever-snaps. As part of a relative-change based force signal interpretation scheme, an effective gradient calibration process is(More)
Robotic failure is all too common in unstructured robot tasks. Despite well designed controllers, robots often fail due to unexpected events. How do robots measure unexpected events? Many do not. Most robots are driven by the senseplan- act paradigm, however more recently robots are working with a sense-plan-act-verify paradigm. In this work we present a(More)