PhD Thesis Proposal

Abstract: A robot that operates efficiently in a team with a human in an unstructured outdoor environment must be able to translate commands from a modality that is intuitive to its operator into actions. This capability is especially important as robots become ubiquitous and interact with untrained users. For this to happen, the robot must [...]

Abstract: A general purpose robot will need to interact with objects in cluttered environments with minimal supervision. Machine learning provides methods that can deal with these complex tasks without explicitly modelling the environment. More recently, deep learning techniques combined with large scale data has revolutionized the fields of computer vision, language processing and reinforcement learning. [...]

Abstract: Robust robotic flight requires tightly coupled perception and control. Conventional approaches employ a SLAM algorithm to infer the most likely trajectory and then generate an occupancy grid map using dense sensor data for planning purposes. In such approaches all the robustness and accuracy costs are offset to the SLAM algorithm; if there are any [...]

Abstract: Imaging sonars have been used for a variety of tasks geared towards increasing autonomy of underwater vehicles: image registration and mosaicing, vehicle localization, object recognition, mapping, and path planning, to name a few. However, the complexity of the image formation has led many algorithms to make the restrictive assumption that the scene geometry is [...]

Abstract: Current non-rigid structure from motion (NRSfM) algorithms are limited with respect to: (i) the number of images, and (ii) the type of shape variability they can handle. This has hampered the practical utility of NRSfM for many applications within vision. Deep Neural Networks (DNNs) are an obvious candidate to help with such issue. However, [...]

Abstract: Portable camera sensor systems are becoming more and more popular in computer vision applications such as autonomous driving, virtual reality, robotics manipulation and surveillance, due to the decreasing expense and size of RGB camera. Despite the compactness and portability of the small baseline vision systems, it is well-known that the uncertainty in range finding [...]

Abstract: Humans have the remarkable ability to create visual worlds far beyond what could be seen by human eye, including inferring the state of unobserved, imagining the unknown, and thinking about diverse possibilities about what lies in the future. Machines lack this inquisitive ability despite the current revolution in machine learning and computer vision. We [...]

Abstract: Humans are arguably one of the most important entities that AI systems would need to understand to be useful and ubiquitous. From autonomous cars observing pedestrians to assistive robots helping the elderly, a large part of this understanding is focused on recognizing human actions, and potentially, their intentions. Humans themselves are quite good at [...]

Abstract: Real-time dense 3D reconstruction of indoor environments has been a popular research field due to its wide application, such as inspection, virtual / augmented reality (VR/AR), and service robotics. While many state-of-the-art algorithms are capable of reconstructing accurate 3D dense models in general indoor scenes, robustness is still an unsolved problem for all of [...]

Abstract: Water ice at the lunar poles could be the most valuable resource beyond planet Earth. However, that value is not foregone, and can only be determined by rovers that evaluate the distributions of abundance, concentration, and characteristics of this ice. The near-term explorations will be solar and unlikely to endure night, and hence are [...]