PhD Thesis Defense
Carnegie Mellon University
Semantic Mapping for Autonomous Navigation and Exploration
Abstract: The last two decades have seen enormous progress in the sensors and algorithms for 3D perception, giving robots the means to build accurate spatial maps and localize themselves in them in real time. The geometric information in these maps is invaluable for navigation while avoiding obstacles, but insufficient, by itself, for robots to robustly [...]
Carnegie Mellon University
Efficient Robot Decision-Making for Achieving Multiple Independent Tasks
Abstract: We focus on robotics applications where a robot is required to accomplish a set of tasks that are partially observable and evolve independently of each other according to their dynamics. One such domain that we target in this work is decision-making for a robot waiter waiting tables at a restaurant. The robot waiter should [...]
Carnegie Mellon University
Decentralized Navigation of Quadrotor Teams in Uncertain Workspaces
Abstract: A fundamental requirement for realizing scalable and responsive real-world multi-robot systems for time-sensitive critical applications such as search and rescue or building clearance is a motion-planning and coordination framework that exhibits three essential properties. The first property is safety that encompasses aspects relating to kinodynamic feasibility and collision-avoidance. The second property is reliability that [...]
Carnegie Mellon University
Bayesian Models for Science-Driven Robotic Exploration
Abstract Planetary rovers allow for science investigations at remote locations. They have traversed many kilometers and made major scientific discoveries. However, rovers spend a considerable amount of time awaiting instructions from mission control. The reason is that they are designed for highly supervised data collection, not for autonomous exploration. The exploration of farther worlds will [...]
Carnegie Mellon University
Heuristics for routing and scheduling of Spatio-temporal type problems in industrial environments
Abstract: Spatio-temporal problems are fairly common in industrial environments. In practice, these problems come with different characteristics and are often very hard to solve optimally. So, practitioners prefer to develop heuristics that exploit mathematical structure specific to the problem for obtaining good performance. In this thesis, we will present work on heuristics for 3 different [...]
Carnegie Mellon University
Relationships in instance segmentation and anomaly detection
Abstract: This thesis primarily covers work on two different tasks in computer vision: (1) anomaly detection and (2) instance segmentation. Anomaly detection is an underexplored unsupervised problem that has existed in many fields. On the other hand, instance (and panoptic) segmentation is a supervised problem that can leverage the powerful data and key developments from [...]
Carnegie Mellon University
Dynamical Model Learning and Inversion for Aggressive Quadrotor Flight
Abstract: Quadrotor applications have seen a surge recently and many tasks require precise and accurate controls. Flying fast is critical in many applications and the limited onboard power source makes completing tasks quickly even more important. Staying on a desired course while traveling at high speeds and high accelerations is difficult due to complex and [...]
Carnegie Mellon University
Person Transfers Between Multiple Service Robots
Abstract: As more service robots are deployed in the world, human-robot interaction will not be limited to one-to-one interactions between users and robots. Instead, users will likely have to interact with multiple robots, simultaneously or sequentially, throughout their day to receive services and complete different tasks. In this thesis, I describe work in which my [...]
Carnegie Mellon University
Understanding, Exploiting and Improving Inter-view Relationships
Abstract: Multi-view machine learning has garnered substantial attention in various applications over recent years. Many such applications involve learning on data obtained from multiple heterogeneous sources of information, for example, in multi-sensor systems such as self-driving cars, or monitoring intensive care patient vital signs at their bed-side. Learning models for such applications can often benefit [...]
Carnegie Mellon University
Human-in-the-loop Control of Mobile Robots
Abstract: Human-in-the-loop control for mobile robots is an important aspect of robot operation, especially for navigation in unstructured environments or in the case of unexpected events. However, traditional paradigms of human-in-the-loop control have relied heavily on the human to provide precise and accurate control inputs to the robot, or reduced the role of the human [...]