Title: Rapid Subsurface Exploration with Multiple Aerial Robots Abstract: This thesis develops a robotic exploration framework that allows for rapid and communication-efficient mapping of unknown environments with a team of aerial robots. Aerial robots can provide rapid and agile mobility in diverse environments where ground mobility is either severely constrained or impossible. However, high-speed flight [...]

Title: BusEdge: Efficient Live Video Analytics for Transit Buses via Edge Computing Abstract: Many vehicles like transit buses are now routinely fitted with cameras. These live visual data are invaluable to achieve real-time traffic monitoring, but it is intractable to handle such a gigantic amount of data either locally or in the cloud due to [...]

Title: Multi-Echo 3D Object Detection Abstract: LiDAR sensors can be used to obtain a wide range of measurement signals other than a simple 3D point cloud, and those signals can be leveraged to improve perception tasks like 3D object detection. A single laser pulse can be partially reflected by multiple objects along its path, resulting [...]

Title: Exemplar free video retrieval.   Abstract: Video retrieval of activities has a wide range of applications. In the traditional mode of operation,  a collection of example videos describing the activities are given and the retrieval technique identifies other samples in a dataset that semantically match the examples provided. However, retrieval using a collection of example [...]

Title: Data-efficient Behavior Prediction for Safe Human-Robot Collaboration.   Abstract: Predicting human behavior is critical to facilitate safe and efficient human-robot collaboration (HRC). However, human behavior is difficult to predict due to the scarcity of human motion data. This work explores using online adaptation, an online approach, and data augmentation, an offline approach, to deal with the [...]

Title: Explainability in navigation policies Abstract: Today's autonomous agents have improved performance with learning and planning algorithms, but the applicability of such agents in the human-inhabited world is confined. Humans find it hard to explain the model's decision-making and thus, may not trust it as a teammate. While working with a machine learning model that […]

Title: Turning Behavior of Running Systems induced by Leg Placement Abstract: Compared to legged robots, animals and humans can perform much faster and larger turns, even when they run at high speeds. Such rapid turns require the body of a runner to reorient dynamically and in synchrony with its redirection during stance. While it is […]

Title: Learning Mental Models of Experts in a Simulated Search and Rescue Scenario   Abstract: Search and Rescue is a task where the rescuers need to be cognitively agile, strategically consistent, and efficient to save as many trapped victims as possible. In a team scenario, the rescuers must additionally coordinate with each other based on […]

Title: Robotic Vision for 3D Modeling and Sizing in Agriculture Abstract: Obtaining accurate perceptual information is a critical component in agricultural robotics since there is a heavy need for interaction with the environment to perform tasks such as pruning, harvesting, and phenotyping. In this thesis, we tackle the problem of perception and 3D modeling in […]

Title: Underground Representations for Robot Localization and Mapping   Abstract: There has been exciting recent progress in using radar as a sensor for robot navigation given its increased robustness to varying environmental conditions. However, within these different radar perception systems, ground penetrating radar (GPR) remains under-explored. By measuring structures beneath the ground, GPR can provide stable features that […]

Title: On combining Reinforcement Learning & Adversarial Training Abstract: Reinforcement Learning (RL) allows us to train an agent to excel at a given sequential decision-making task by optimizing for a reward signal. Adversarial training involves a joint optimization scheme where an agent and an adversary compete against each other. In this work, we explore some […]

Title: Physics-based object-aware ego-centric human pose estimation Abstract: We investigate the roles of body kinematics, dynamics, and objects for 3D human pose estimation using a head-mounted camera. Human kinematics models play a key role in encoding the natural range of human motion, while dynamics models can react to the spatial arrangement between humans and objects […]