PhD Thesis Defense
Carnegie Mellon University
Provably Constant-Time Motion Planning
Abstract: In many robotic applications, including logistics and manufacturing, robots often operate in semi-structured environments and perform highly repetitive manipulation tasks. Additionally, large parts of these environments are static most of the time. Fast and reliable motion planning is one of the key elements that ensure efficient operations in such environments. A very common example [...]
Carnegie Mellon University
Planning to Optimize and Learn Reward in Navigation Tasks in Structured Environments with Time Constraints
Abstract: Planning problems in which an agent must perform tasks for reward by navigating its environment while constrained by time and location have a wide variety of applications in robotics. Many real-world environments in which such planning problems apply, such as office buildings or city streets, are very structured. They consist of passages with notable [...]
Carnegie Mellon University
Robust and Scalable Perception For Autonomy
Abstract: Autonomous mobile robots have the potential to drastically improve the quality of our daily life. For example, self-driving vehicles could make transportation safer and more affordable. To navigate complex environments, such robots need a perception system that translates raw sensory data to high-level understanding. This thesis focuses on two fundamental challenges in learning such [...]
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 [...]