MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Jay Patrikar – MSR Thesis Talk

Zoom link: https://cmu.zoom.us/j/93391276533?pwd=RTM4NTc0cTJETmRudGcwenNCSVgzdz09 Title: Wind-Field Estimation and Curvature Continuous Path Planning for Low Altitude Urban Aerial Mobility Abstract: Unmanned Aerial Vehicles (UAVs) operating in dense urban areas need the ability to generate wind-aware collision-free, smooth, dynamically feasible trajectories between two locations. The complex and high-rise structure of the modern urban landscape affects the wind flow [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Benjamin Freed – MSR Thesis Talk

Where?:https://cmu.zoom.us/j/96355036481?pwd=OCtBeWZpMnZsZzFlRkJWc2dkZW5qUT09   Title: Discrete Communication Learning via Backpropagation for Distributed Computing on Bandwidth-Limited Communication Networks   Abstract: Efficient inter-agent communication is an important requirement for both cooperative multi-agent robotics tasks, as well as distributed computing.  In both of these domains, the rate at which information can be transferred between robots or computing nodes is often [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Tanvir Parhar – MSR Thesis Talk

Zoom Link:https://cmu.zoom.us/j/3399055387 Title: Applications of Deep Learning for Robotic Agriculture.   Abstract: Agricultural automation is a varied and challenging field, with tasks ranging from detection to sizing and from manipulation to navigation. These are also precursors to effective plant breeding and management. Making plant measurements by manually scouting is labor-intensive and intractable at large scale. [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Hitesh Arora – MSR Thesis Talk

Zoom link: https://cmu.zoom.us/j/4937138807   Title: Off-Policy Reinforcement Learning for Autonomous Driving   Abstract: Modern autonomous driving systems continue to face the challenges of handling complex and variable multi-agent real-world scenarios. Some subsystems, such as perception, use deep learning-based approaches to leverage large amounts of data to generalize to novel scenes. Other subsystems, such as planning [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Scott Sun – MSR Thesis Talk

Zoom link: https://cmu.zoom.us/j/93097644031?pwd=RzZVSXEvdE5zZ0RDaU9FdmRUMU1vQT09 Title: Accurate Orientation Estimates for Deep Inertial Odometry Abstract: Many smartphone applications use inertial measurement units (IMUs) to sense movement, but the use of these sensors for pedestrian localization can be challenging due to their noise characteristics. Recent deep inertial odometry approaches to pedestrian navigation have demonstrated the increasing feasibility of inertial navigation. However, [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Allen Cheng – MSR Thesis Talk

Zoom link: https://cmu.zoom.us/j/6056258382   Title: Search-Based Planning with Extend Operator   Abstract: Sampling-based approaches are often favored in robotics for high-dimensional motion planning for their fast coverage of the search space. However, at best they offer asymptotic guarantees on completeness and solution quality, and returned paths are typically unpredictable due to their inherent stochasticity. By [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Chenfeng Tu – MSR Thesis Talk

Location: https://cmu.zoom.us/j/96696044200?pwd=MVl4aUpiZlYvYlRwRmF1SVBUeGx6Zz09   Title: On-the-fly Targetless Extrinsics Calibration For Multi-Stereo Systems Without Field-of-View Overlap Abstract: In this talk, we propose an on-the-fly extrinsics calibration method for stereo pairs lacking overlapping field of view that is robust to visual odometry errors. Multi-stereo systems are becoming increasingly popular because of their large field of view (FoV) that benefits [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Shuoqi Chen – MSR Thesis Talk

Zoom link: https://cmu.zoom.us/j/9608506704   Title: Towards Geometric Motion Planning for 3-link Kinematic Systems   Abstract: Geometric mechanics offers a powerful mathematical framework for studying locomotion for mobile systems. Despite the well-established literature, challenges remain when using geometric mechanics to design gaits for robots made of multi-link chain; in this thesis, we look at two of them. First, [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Robot Deep Reinforcement Learning: Tensor State-Action Spaces and Auxiliary Task Learning with Multiple State Representations

Zoom Link Abstract: A long standing goal of robotics research is to create algorithms that can automatically learn complex control strategies from scratch. Part of the challenge of applying such algorithms to robots is the choice of representation. Reinforcement Learning (RL) algorithms have been successfully applied to many different robotic tasks such as the Ball-in-a-Cup [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Raunaq Bhirangi – MSR Thesis Talk

Zoom link: https://cmu.zoom.us/j/93803046130?pwd=dE5LU21lakcxNjBmZ0EvVDdNOWswdz09   Title: Learning Families of Behaviors for Legged Locomotion using Model-Free Deep Reinforcement Learning   Abstract: Conventional planning and control of highly articulated legged robots is challenging because of the high dimensionality of the state space, and such conventional techniques normally produce a single point solution. In this work, we present a [...]