MSR Thesis Talk: Joshua Spisak
Title: Stochastic Optimization for Autonomous Navigation, Leveraging Parallel Computation Abstract: Stochastic Optimal Control (SOC) is a framework that allows disturbances and uncertainty in system models to be accounted for in its optimization framework. Despite accounting for this uncertainty, many first and second order methods for solving SOC problems are subject to local minima and are [...]
Carnegie Mellon University
MSR Thesis Talk: Yimin Tang
Title: Solving Multi-Agent Target Assignment and Path Finding with a Single Constraint Tree Abstract: Multi-Agent Path Finding (MAPF) and Combined Target-Assignment and Path-Finding problem (TAPF) arise in many applications such as robotics, computer gaming, warehouse automation and traffic management at road intersections. Combined Target-Assignment and Path-Finding problem (TAPF) requires simultaneously assigning targets to agents and [...]
MSR Thesis Talk: Xuxin Cheng
Title: Learning Legged Robot Agility: Sim-to-Real and Beyond Abstract: Legged robotics has seen significant advancements in both manipulation and locomotion. However, there remain significant gaps compared to their biological counterparts, particularly in energy efficiency, natural motion, and the capacity for agile skills. This thesis primarily focuses on two aspects: the unified control of legged manipulators [...]
MSR Thesis Talk: Harry Freeman
Title: Computer Vision-Based Phenotyping in Agriculture: Leveraging Semantic Information for Non-Destructive Small Crop Analysis Abstract: Fast and reliable non-destructive phenotyping of plants plays an important role in precision agriculture, as the information enables farmers to make real-time crop management decisions without affecting yield. To non-destructively phenotype crops, computer and stereo-vision based methods are commonly used, [...]
MSR Thesis Talk: Nishant Mohanty
Title: Multi-Robot Control using Control Barrier Functions: Theory and Application Abstract: Control Barrier Functions (CBFs) have emerged as a powerful theoretical tool for designing controllers with provable safety guarantees. This work presents a novel methodology that leverages CBFs to synthesize controllers for multi-robot coordination. Two multi-agent use cases are explored, i.e., a) Non-Cooperative Herding and [...]
MSR Thesis Talk: Yuyao Shi
Title: A Learning Approach to Understand How Spinal Cord Learns Multiple Behaviors Abstract: The spinal cord plays a crucial role in the control of human locomotion, generating motor patterns and coordinating reflex responses to sensory signals. Although this spinal control is traditionally viewed as a simple relay system, more recent neurophysiological evidence points to a [...]
Carnegie Mellon University
MSR Thesis Talk: FNU Abhimanyu
Title: Improving Robotic Ultrasound AI Using Optical Flow Abstract: Ultrasound is an important modality for medical intervention such as vascular access because it is safe, portable, and low-cost. However, ultrasound scanning requires trained sonographers who are scarce, and it can be challenging to perform ultrasound examinations in disaster or battlefield scenarios. This motivates us to automate [...]
Vision-based Proprioceptive and Tactile Sensing for Soft Robots
Abstract: Soft robotic manipulators present many unique advantages in difficult manipulation tasks. The inherent compliance of soft robots' constituent deformable material makes them safe and reliable in delicate tasks such as harvesting fruit and assisting in household work. To address challenges in proprioceptive and tactile sensing for soft robots, we present a family of vision-based [...]
MSR Thesis Talk: Lucas Casanova De Oliveira Nogueira
Title: SuperLoop: a LIDAR-based SLAM Back-end for Underground Exploration Abstract: Robots deployed in underground scenarios require a SLAM system that can handle a variety of challenges, such as the absence of GPS, large scale maps, bad illumination, and geometrically degenerate environments. It is nearly impossible for any SLAM solution to handle all these challenges perfectly, specially [...]
Learning via Visual-Tactile Interaction
Abstract: Humans learn by interacting with their surroundings using all of their senses. The first of these senses to develop is touch, and it is the first way that young humans explore their environment, learn about objects, and tune their cost functions (via pain or treats). Yet, robots are often denied this highly informative and [...]