PhD Thesis Defense
Carnegie Mellon University
Understanding and Mitigating Biases in Evaluation
Abstract: There are many problems in real life that involve collecting and aggregating evaluation from people, such as hiring, peer grading and conference peer review. In this thesis, we focus on three sources of biases that arise in such problems, and propose methods to mitigate them. First, we study human bias, that is, the bias [...]
Carnegie Mellon University
Towards Safe and Resilient Autonomy in Multi-Robot Systems
Abstract: Autonomous systems such as robotic systems are envisioned to co-exist with humans in our daily lives, from household service to large-scale warehouse logistics, agricultural monitoring, and smart city. Reliable interactions among robots and humans require provably correct guarantees about safety and performance when designing robot behaviors. While traditional approaches for safety and performance analysis [...]
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 [...]