MSR Speaking Qualifier

Zoom Link: https://cmu.zoom.us/j/7518832261 Title: System Design, Modelling, and Control for an Off-Road Autonomous Ground Vehicle Abstract: Autonomy in passenger road vehicles has long been a goal for many research groups and companies, and there has been a significant amount of focus on achieving this endeavour. A lesser focused upon area is the task of precise autonomous [...]

Zoom Link: https://cmu.zoom.us/j/5523238059   Title: Robust Instance Tracking via Uncertainty Flow   Abstract: Current state-of-the-art trackers often fail due to distractors and large object appearance changes. In this work, we explore the use of dense optical flow to improve tracking robustness. Our main insight is that, because flow estimation can also have errors, we need [...]

Zoom Link: https://cmu.zoom.us/j/8978517404 Title: Visual Assessment for Non-Disruptive Object Extraction Abstract: Robots operating in human environments need to perform a variety of dexterous manipulation tasks on object arrangements that have complex physical support relationships, e.g. procuring utensils from a large pile of dishes, grabbing a bottle from a stuffed fridge, or fetching a book from a loaded [...]

Location: https://cmu.zoom.us/j/98262481359?pwd=dnN4UERmQlF6dVVROTQ1czYrU215UT09 Title: Efficient Multiresolution Scrolling Grid for MAV Obstacle Avoidance Abstract: In this talk, we propose the use of an efficient, structured multiresolution representation for robot mapping and planning.  We focus on expanding the sensor range of dense local grids for memory-constrained platforms.  While multiresolution data structures have been proposed previously, we avoid processing [...]

Zoom link: https://cmu.zoom.us/j/3388909661 Title: On-Policy Reinforcement Learning for Learning to Drive in Urban Settings Abstract: Traditional autonomous vehicle pipelines that follow a modular approach have been very successful in the past both in academia and industry, which has led to autonomy deployed on road. Though this approach provides ease of interpretation, its generalizability to unseen [...]

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 [...]

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 [...]

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. [...]

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 [...]

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, [...]