PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Auto-generated Manipulation Primitives

Abstract: The central theme in robotic manipulation is that of the robot interacting with the world through physical contact. We tend to describe that physical contact using specific words that capture the nature of the contact and the action, such as grasp, roll, pivot, push, pull, tilt, close, open etc. We refer to these situation-specific [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Learning 3D Registration and Reconstruction from the Visual World

Abstract: Humans learn to develop strong senses for 3D geometry by looking around in the visual world. Through pure visual perception, not only can we recover a mental 3D representation of what we are looking at, but meanwhile we can also recognize where we are looking at the scene from. Finding the 3D scene representation [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Development of an Agile and Dexterous Balancing Mobile Manipulator Robot

Abstract: The proposed thesis work focuses on the design and control of a new unique agile and dexterous mobile manipulator, the Carnegie Mellon University (CMU) ballbot. The CMU ballbot is a human-sized dynamically stable mobile robot that balances on a single ball. We present the development and integration of a new pair of seven-degree-of-freedom (7-DOF) [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Shengcao Cao

Title: Efficient Model Performance Estimation via Feature Histories Abstract: An important step in the task of neural network design, such as hyper-parameter optimization (HPO) or neural architecture search (NAS), is the evaluation of a candidate model's performance. Given fixed computational resources, one can either invest more time training each model to obtain more accurate estimates [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Steven Lee

Title: Learning to Represent and Accurately Arrange Food Items   Abstract: Arrangements of objects are commonplace in a myriad of everyday scenarios, such as decorations at one’s home, displays at museums, and plates of food at restaurants. An efficient personal robot should be able to learn how to robustly recreate an arrangement using only a few [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Amrita Sawhney

Title: Learning to Perceive and Manipulate Diverse Food Materials Through Interaction Abstract: The home kitchen environment presents many challenges for an autonomous cooking robot, such as the deformability of food items, the wide range of material properties of food, and the complex interaction dynamics involved in food manipulation tasks. Material properties are important when interacting [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Haidar Jamal

Zoom

Title: Localization for Lunar Micro-Rovers   Abstract: This talk presents an avionics and localization system that enables a lunar micro-rover to navigate autonomously. This system is important for the latest class of small, low-powered, and fast robots going to the Moon in search of polar ice. The first component of the system is an Extended [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

PoseIt: A Visual-Tactile Dataset of Holding Poses for Grasp Stability Analysis

Abstract: When humans grasp objects in the real world, we often move our arm to hold the object in a different pose where we can use it. In contrast, typical lab settings only study the stability of the grasp immediately after lifting, without any subsequent re-positioning of the arm. However, an object’s stability could vary [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Planning to Minimize Human and Robot Efforts Over Tasks

Abstract: It is not feasible to pre-program robots a priori for every possible task they may encounter in unstructured domains. Upon encountering a task that a robot can't solve, one common strategy is to teach it new skills via demonstrations. However, demonstrating a task can often be more cumbersome than performing the task directly. This [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Akash Sharma

Title: Incorporating Semantic Structure in SLAM Abstract: For robots to understand the environment they interact with, a combination of geometric information and semantic information is imperative. In this talk, I propose a fast and scalable Simultaneous Localization and Mapping (SLAM) system that represents indoor scenes as a graph of semantic objects. Leveraging the observation that [...]