PhD Thesis Defense
Creative Robotic Systems for Talent-based Learning
Event Location: GHC 4405Abstract: In recent years, the U.S. educational system has fallen short in training the technology innovators of the future. To do so, we must give students the experience of designing and creating technological artifacts, rather than relegating students to the role of technology consumers, and must provide educators with opportunities and professional [...]
The theory, implementation, and evaluation of spring mass running on ATRIAS, a bipedal robot
Event Location: NSH 3305Abstract: We expect legged robots to be highly mobile. Human walking and running can execute quick changes in speed and direction, even on non-flat ground. Indeed, analysis of simplified models shows that these quantities can be tightly controlled by adjusting the leg placement between steps, and that leg placement can also compensate [...]
Improving Prediction of Traversability for Planetary Rovers Using Thermal Imaging
Event Location: GHC 4405Abstract: The most significant mobility challenges that planetary rovers encounter are compounded by loose, granular materials that cause slippage and sinkage on slopes or are deep enough to entrap a vehicle. The inability of current technology to detect loose terrain hazards has caused significant delays for rovers on both the Moon and [...]
Safe, Efficient, and Robust Predictive Control of Constrained Nonlinear Systems
Vishnu R. Desaraju Carnegie Mellon University April 12, 2017, 2:00 p.m., NSH 1305 Abstract As autonomous systems are deployed in increasingly complex and uncertain environments, safe, accurate, and robust feedback control techniques are required to ensure reliable operation. Accurate trajectory tracking is essential to complete a variety of tasks, but this may be difficult if [...]
Seungmoon Song: The Development, Evaluation and Applications of a Neuromechanical Control Model of Human Locomotion
Seungmoon Song Ph.D. Thesis Defense Abstract: The neural control of human locomotion is not fully understood. As current experimental techniques provide only partial and indirect access to the neural control network, our understanding remains fragmentary with large gaps between detectable neural circuits and measurable behavioral data. Neuromechanical simulation studies can help bridging these gaps. By [...]
Juan Pablo Mendoza: Regions of Inaccurate Modeling for Robot Anomaly Detection and Model Correction
Juan Pablo Mendoza Ph.D. Thesis Defense Abstract: To make intelligent decisions, robots often use models of the stochastic effects of their actions on the world. Unfortunately, in complex environments, it is often infeasible to create models that are accurate in every plausible situation, which can lead to suboptimal performance. This thesis enables robots to reason [...]
Reasoning About Spatial Patterns of Human Behavior During Group Conversations with Robots
Abstract: The goal of this dissertation is to develop computational models for robots to detect and sustain the spatial patterns of behavior that naturally emerge during free-standing group conversations with people. These capabilities have often been overlooked by the Human-Robot Interaction (HRI) community, but they are essential for robots to appropriately interact with and around [...]
Acting under Uncertainty for Information Gathering and Shared Autonomy
Abstract: Acting under uncertainty is a fundamental challenge for any decision maker in the real world. As uncertainty is often the culprit of failure, many prior works attempt to reduce the problem to one with a known state. However, this fails to account for a key property of acting under uncertainty: we can often gain [...]
Situational Awareness and Mixed Initiative Markup for Human-Robot Team Plans
Abstract: As robots become more reliable and user interfaces (UI) become more powerful, human-robot teams are being applied to more real world problems. Human-robot teams offer redundancy and heterogeneous capabilities desirable in scientific investigation, surveillance, disaster response, and search and rescue operations. Large teams are overwhelming for a human operator, so systems employ high level [...]
Discovering and Leveraging Visual Structure for Large-scale Recognition
Abstract: Our visual world is extraordinarily varied and complex, but despite its richness, the space of visual data may not be that astronomically large. We live in a well-structured, predictable world, where cars almost always drive on roads, sky is always above the ground, and so on. As humans, the ability to learn this structure [...]