Learning to Reconstruct 3D Humans
Abstract: Recent advances in 2D perception have led to very successful systems, able to estimate the 2D pose of humans with impressive robustness. However, our interactions with the world are fundamentally 3D, so to be able to understand, explain and predict these interactions, it is crucial to reconstruct people in 3D. In this talk, I [...]
Carnegie Mellon University
Eye Gaze for Assistive Manipulation
Abstract: Full robot autonomy is the traditional goal of robotics research. To work in a human-inhabited world, however, robots will often need to collaborate with humans. Many scenarios require human users to teleoperate robots to perform tasks, a paradigm that appears everywhere from space exploration, to disaster recovery, to assistive robotics. This collaboration enables tasks [...]
CANCELLED
Abstract: Before learning robots can be deployed in the real world, it is critical that probabilistic guarantees can be made about the safety and performance of such systems. In recent years, safe reinforcement learning algorithms have enjoyed success in application areas with high-quality models and plentiful data, but robotics remains a challenging domain for scaling [...]
Deep Learning for Understanding Dynamic Visual Data
Abstract: Perceiving dynamic environments from visual inputs allows autonomous agents to understand and interact with the world and is a core topic in Artificial Intelligence. The success of deep learning motivates us to apply deep learning techniques to the perception of dynamic visual data. However, how to design and apply deep neural networks to effectively [...]
Carnegie Mellon University
Stability-Centric Mechanics for Rigid Body Manipulation
Abstract: The repertoire of human manipulation is filled with creative use of contacts to move the object about the hand and the environment. It’s the combination of these skills that makes human manipulation dexterous. However, in most robotic applications the robot just fix all contact points on the object and do grasping. Reliable robot manipulation [...]
Optimizing for coordination with people
https://youtu.be/AQ-w5o2oGI8 Abstract: From autonomous cars to quadrotors to mobile manipulators, robots need to co-exist and even collaborate with humans. In this talk, we will explore how our formalism for decision making needs to change to account for this interaction, and dig our heels into the subtleties of modeling human behavior -- sometimes strategic, often irrational, [...]
Analyzing Grasp Contact via Thermal Imaging
Abstract: Grasping and manipulating objects is an important human skill. Because contact between hand and object is fundamental to grasping, measuring it can lead to important insights. However, observing contact through external sensors is challenging because of occlusion and the complexity of the human hand. I will discuss the use of thermal cameras to capture [...]
Numerical Methods for Things That Move: From Quadrupeds to Starships
Abstract: Recent advances in motion planning and control have led to dramatic successes like SpaceX’s rocket landings and Boston Dynamics’ humanoid robot acrobatics. However, the underlying numerical methods used in these applications are typically decades old, not tuned for high performance on planning and control problems, and are often unable to cope with the types [...]
Carnegie Mellon University
Combining Multiple Heuristics: Studies on Neighborhood-base Heuristics and Sampling-based Heuristics
Abstract: This thesis centers on the topic of how to automatically combine multiple heuristics. For most computationally challenging problems, there exist multiple heuristics, and it is generally the case that any such heuristic exploits only a limited number of aspects among all the possible problem characteristics that we can think of, and by definition, is [...]