MSR Speaking Qualifier

Title: Smartphone localization for Indoor Pedestrian Navigation Abstract: Global positioning system (GPS) interfacing with applications such as Google Maps has proven very useful for navigation in outdoor open settings. However in crowded metropolitan environments with high rise buildings or in indoor settings, GPS quickly becomes unreliable. Using sensors found on commodity smartphones to perform accurate [...]

Title: Distributed Reinforcement Learning for Autonomous Driving Abstract: Due to the complex and safety-critical nature of autonomous driving, recent works typically test their ideas on simulators designed for the very purpose of advancing self-driving research. Despite the convenience of modeling autonomous driving as a trajectory optimization problem, few of these methods resort to online reinforcement [...]

Title: Ride Comfort-Aware Visual Navigation via Self-Supervised Learning Abstract: Under shared autonomy, wheelchair users expect vehicles to provide safe and comfortable rides while following users’ high-level navigation plans. To find such a path, vehicles negotiate with different terrains and assess their traversal difficulty. Most prior works model surroundings either through geometric representations or semantic classifications, [...]

Title: Fast 6D Object Pose Refinement via Deep Texture Rendering   Abstract: We present RePOSE, a fast iterative refinement method for 6D object pose estimation. Prior methods perform refinement by feeding zoomed-in input and rendered RGB images into a CNN and directly regressing an update of a refined pose. Their runtime is slow due to the [...]

Abstract: Detect-and-Avoid (DAA) capabilities are critical for autonomous operations of small unmanned aircraft systems (sUAS). Traditionally DAA systems for large aircraft have been ground and radar-based. Due to the size, weight, and power (SWaP) constraints of sUAS, current DAA systems rely mainly on vision-based sensors and ADS-B (Automatic Dependent Surveillance-Broadcast) transponders. However, not all flying [...]

Title: Preprocessing-based Methods for Robotic Manipulation Abstract: Robotic manipulation is a key problem for several applications such as welding, pick-and-place, and automated assembly. However, motion planning for manipulation can be computationally expensive as it requires planning in the high-dimensional configuration space of the manipulator. Additionally, task-specific constraints such as strict time limits or constraints on end-effector [...]

Title: Socially-Aware Trajectory Prediction Guided by Motion Patterns Abstract: As intelligent robots across domains start collaborating with humans in shared environments, e.g., urban settings and terminal airspace, algorithms that enable them to reason over human motion and intent are important to enable seamless and safe interplay. In our work, we study human intent by focusing on the [...]

Date: Tuesday, July 19, 2022 Time: 9:00 AM - 10:00 AM ET Location: Newell-Simon Hall (NSH) 3305 Title: Detect Active Object in a Sequential Voting Process Abstract: A key component of understanding hand-object interactions is the ability to identify the active object -- the object that is being manipulated by the human hand. In order to accurately localize the [...]

Title: Real-Time Visual Localization System in Changing and Challenging Environments via Visual Place Recognition   Abstract: Localization is one of the fundamental capabilities to guarantee reliable robot autonomy. Many excellent Visual-Inertial and LiDAR-based algorithms have been developed to solve the localization problem. However, deploying these methods on a real-time portable device is challenging due to high [...]

Title: Seeing the Unseen: Closed-loop Occlusion Reasoning for Cloth Manipulation Robotic manipulation of cloth remains challenging due to the complex dynamics of cloth, lack of a low-dimensional state representation, and self-occlusions. Particularly, self-occlusion makes it difficult to estimate the full state of the cloth, which poses significant challenges to policy learning and dynamics modeling. Ideally, [...]