PhD Speaking Qualifier
Search-based Path Planning for a High Dimensional Manipulator in Cluttered Environments Using Optimization-based Primitives
Abstract: In this work we tackle the path planning problem for a 21-dimensional snake robot-like, navigating a cluttered gas turbine for the purposes of inspection. Heuristic search-based approaches are effective planning strategies for common manipulation domains. However, their performance on high-dimensional systems is heavily reliant on the effectiveness of the action space and the heuristics [...]
Vision-Based Tactile Sensor Design using Physics Based Rendering
Abstract: Tactile sensing has seen a rapid adoption with the advent of vision-based tactile sensors. Vision-based tactile sensors provide high resolution, compact and inexpensive data to perform precise in-hand manipulation and human-robot interaction. However, the simulation of tactile sensors is still a challenge. Simulation is a critical tool in the development of robotic systems. In [...]
Kernel Density Decision Trees
Abstract We propose kernel density decision trees (KDDTs), a novel fuzzy decision tree (FDT) formalism based on kernel density estimation that improves the robustness of decision trees and ensembles and offers additional utility. FDTs mitigate the sensitivity of decision trees to uncertainty by representing uncertainty through fuzzy partitions. However, compared to conventional, crisp decision trees, [...]
Energy-based Joint Pose Estimation for 3D Reconstruction
Abstract: In this talk, I will describe a data-driven method for inferring camera poses given a sparse collection of images of an arbitrary object. This task is a core component of classic geometric pipelines such as structure-from-motion (SFM), and also serves as a vital pre-processing requirement for contemporary neural approaches (e.g. NeRF) to object reconstruction. [...]
NeRF for Robotics
Abstract: In this talk I'll describe how recent advances in neural rendering and novel view synthesis - namely NeRF - can be leveraged by robotic agents to improve performance in manipulation tasks. Specifically, I'll argue that NeRF can enable robotic policies to: (1) generalize to new viewpoints; (2) perceive specular and reflective surfaces in a [...]
Robust Reinforcement Learning via Genetic Curriculum
Abstract: Achieving robust performance is crucial when applying deep reinforcement learning (RL) in safety critical systems. Some of the state of the art approaches try to address the problem with adversarial agents, but these agents often require expert supervision to fine tune and prevent the adversary from becoming too challenging to the trainee agent. While [...]
Mouth Haptics in VR using a Headset Ultrasound Phased Array
Abstract: This talk is the same one I will be presenting at the ACM CHI Conference on Human Factors in Computing Systems on May 2nd. Paper abstract: Today’s consumer virtual reality (VR) systems offer limited haptic feedback via vibration motors in handheld controllers. Rendering haptics to other parts of the body is an open challenge, [...]
TIGRIS: An Informed Sampling-based Algorithm for Informative Path Planning
Abstract: In this talk I will present our sampling-based approach to informative path planning that allows us to tackle the challenges of large and high-dimensional search spaces. This is done by performing informed sampling in the high-dimensional continuous space and incorporating potential information gain along edges in the reward estimation. This method rapidly generates a [...]
Trajectory Optimization for Thermally-Actuated Soft Planar Robot Limbs
Abstract: Practical use of robotic manipulators made from soft materials requires generating and executing complex motions. We present the first approach for generating trajectories of a thermally-actuated soft robotic manipulator. Based on simplified approximations of the soft arm and its antagonistic shape-memory alloy actuator coils, we justify a dynamics model of a discretized rigid manipulator [...]
Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis
Abstract: Neural networks can represent and accurately reconstruct radiance fields for static 3D scenes (e.g., NeRF). Several works extend these to dynamic scenes captured with monocular video, with promising performance. However, the monocular setting is known to be an under-constrained problem, and so methods rely on data-driven priors for reconstructing dynamic content. We replace these [...]
Combining vision-based tactile, proximity, and global sensing for robotic manipulation
Abstract: I will begin by describing our work on visual servoing a manipulator and localizing objects using a robot-mounted suite of vision and vision-based tactile sensors, our results, algorithms used, and lessons learned. We show that by collocating tactile, and global (e.g. an RGB(D) camera) sensors, our setup can perform better than using each type [...]
Design, Modeling and Control for a Tilt-rotor VTOL UAV in the Presence of Actuator Failure
Abstract: Providing both the vertical take-off and landing capabilities and the ability to fly long distances to aircraft opens the door to a wide range of new real-world aircraft applications while improving many existing applications. Tiltrotor vertical take-off and landing (VTOL) unmanned aerial vehicles (UAVs) are a better choice than fixed-wing and multirotor aircraft for [...]
Lessons Learned from Creating Low-Cost Dexterous Soft Robot Hands
Abstract: Soft robot hands have shown promising results when it comes to dexterous grasping and manipulation. Compared to their rigid counterparts, soft hands can be manufactured for a fraction of the cost and offer robustness to uncertainty due to their inherent compliance. Unfortunately, the design and fabrication of soft robot hands is still a time-consuming [...]
Modern Trajectory Forecasting Methods Lack Social Awareness
Abstract: We present a thorough evaluation and analysis of state-of-the-art (SOTA) human trajectory forecasting methods with respect to metrics for safe and socially-aware prediction, e.g., collision rate, in addition to traditional displacement metrics, e.g., average displacement error. First, we introduce a system for trajectory classification which is used to evaluate the strengths and weaknesses of [...]
Learning to perform dynamic and interactive tasks using structural and algorithmic priors
Abstract: Everyday human tasks such as picking up an object in one smooth motion, pushing a heavy door using the momentum of our bodies or pushing off a wall to quickly turn a corner involve complex dynamic interactions between the human and the environment, as well as switching dynamics when the robot makes and breaks [...]
Simple Shape Descriptors for Retinal Surface Estimation using a Laser-Aiming Beam
Abstract: Retinal surgery procedures like epiretinal membrane peeling and retinal vein cannulation require surgeons to manipulate very delicate structures in the eye with little room for error. Many robotic surgery systems have been developed to help surgeons and enforce safeguards during these demanding procedures. One essential piece of information that is required to create and [...]
Affective Robot Behavior Improves Learning in a Sorting Game
Abstract: Nonverbal communication in the field of education can allow teachers to emotionally support their students and improve educational experience and performance. Robot nonverbal movements have been shown to improve both subjective experiences and task performance, and this work investigates whether affective robot behavior can improve human learning. This is tested using an online sorting [...]