Student Talks

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 [...]

Title: Detecting Invisible People   Abstract: Monocular object detection and tracking have improved drastically in recent years, but rely on a key assumption: that objects are visible to the camera. Many offline tracking approaches reason about occluded objects post-hoc, by linking together tracklets after the object re-appears, making use of reidentification (ReID). However, online tracking [...]

work, we address the problem of goal-directed cloth manipulation, a challenging task due to the deformability of cloth. Our insight is that optical flow, a technique normally used for motion estimation in video, can also provide an effective representation for corresponding cloth poses across observation and goal images. We introduce FabricFlowNet (FFN), a cloth manipulation [...]

Title: Towards Practical Ultrasound AI Across Real-World Patient Diversity Abstract: In the case of high-tempo, traumatic scenarios on the battlefield, real-time ultrasound (US) imaging serves as an enabler for countless possible robotic interventions. Having the ability to automatically segment anatomical landmarks in the body, such as arteries, veins, ligaments, and veins, for percutaneous procedures remains [...]