MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Yaadhav Raaj MSR Thesis Talk

Title: Exploiting Uncertainty in Triangulation Light Curtains for Object Tracking and Depth Estimation   Abstract: Active sensing through the use of Adaptive Depth Sensors is a nascent field, with potential in areas such as Advanced driver-assistance systems (ADAS). One such class of sensor is the Triangulation Light Curtain, which was developed in the Illumination and Imaging [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Active Vision: Autonomous Aerial Cinematography with Learned Artistic Decision-Making

Abstract: Aerial cinematography is revolutionizing industries that require live and dynamic camera viewpoints such as entertainment, sports, and security. Fundamentally, it is a tool with immense potential to improve human creativity, expressiveness, and sharing of experiences. However, safely piloting a drone while filming a moving target in the presence of obstacles is immensely taxing, often [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Fine-Tuning Offline Reinforcement Learning with Model-Based Policy Optimization

Abstract: In offline reinforcement learning (RL), we attempt to learn a control policy from a fixed dataset of environment interactions. This setting has the potential benefit of allowing us to learn effective policies without needing to collect additional interactive data, which can be expensive or dangerous in real-world systems. However, traditional off-policy RL methods tend [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Zhipeng Bao

Title: Introducing Generative Models to Facilitate Multi-Task Visual Learning Abstract: Motivated by multi-task learning of shared feature representations, this talk considers a novel problem of learning a shared generative model that can facilitate multi-task learning. We present two systems to utilize generative modeling for other visual tasks. The first system focuses on learning a generative [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Shanshan Jessy Xie

TBA

Title: GPU based perception via search for object pose estimation with RGB data   Abstract: Known object pose estimation is essential for a robot to interact with the real world.  It is the first and fundamental task if the robot wants to manipulate the object.  This problem is particularly challenging when the environment is complicated [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Accelerating Numerical Methods for Optimal Control

Abstract: Many modern control methods, such as model-predictive control, rely heavily on solving optimization problems in real time. In particular, the ability to efficiently solve optimal control problems has enabled many of the recent breakthroughs in achieving highly dynamic behaviors for complex robotic systems. The high computational requirements of these algorithms demand novel algorithms tailor-suited [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Modeling Coupled Human-Robot Motion for Provable Safety

Abstract: Guide robots that help users who are blind or low vision navigate through crowds and complex environments show promise for improving accessibility in public spaces. These robots must provide real-time safety guarantees for the users, which requires accurate modeling of their behavior in the context of closely coupled human-robot motion. This model must also [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk – Mosam Dabhi

Title: Multi-view NRSfM: Affordable setup for high-fidelity 3D reconstruction   Abstract: Triangulating a point in 3D space should only require two corresponding camera projections. However in practice, expensive multi-view setups -- involving tens sometimes hundreds of cameras -- are required to obtain the high fidelity 3D reconstructions necessary for many modern applications. In this talk, we argue [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Robust Object Representations for Robot Manipulation

Abstract: As robots become more common in our daily lives, they will need to interact with many different environments and countless types of objects. While we, as humans, can easily understand an object after seeing it only once, this task is not trivial for robots. Researchers have, for the most part, been left with two [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Diminished Reality for Close Quarters Robotic Telemanipulation

Abstract: In robot telemanipulation tasks, the robot itself can sometimes occlude a target object from the user's view. We investigate the potential of diminished reality to address this problem. Our method uses an optical see-through head-mounted display to create a diminished reality illusion that the robot is transparent, allowing users to see occluded areas behind [...]