Student Talks
Carnegie Mellon University
Towards Reconstructing Non-rigidity from Single Camera
Abstract: In this talk we will discuss how to infer 3D from images captured by a single camera, without assuming the target scenes / objects being static. The non-static setting makes our problem ill-posed and challenging to solve, but is vital in practical applications where target-of-interest is non-static. To solve ill-posed problems, the current trend [...]
MSR Thesis Talk: Sarvesh Patil
Title: Soft Delta Robots for Dexterous Manipulation Abstract: Dexterous manipulation capabilities of end-effectors afford us a wide range of strategies for fine-grained manipulation tasks. Recent utilization of readily available materials like soft filaments and silicone elastomers has enabled the development of low-cost mechanically intelligent robotic manipulators. This is important for democratizing robot manipulation and increasing [...]
Large Scale Dense 3D Reconstruction via Sparse Representations
Abstract: Dense 3D scene reconstruction is in high demand today for view synthesis, navigation, and autonomous driving. A practical reconstruction system inputs multi-view scans of the target using RGB-D cameras, LiDARs, or monocular cameras, computes sensor poses, and outputs scene reconstructions. These algorithms are computationally expensive and memory-intensive due to the presence of 3D data. [...]
MSR Thesis Talk: Fan Yang
Title: Exploring Safe Reinforcement Learning for Sequential Decision Making Abstract: Safe Reinforcement Learning (RL) focuses on the problem of training a policy to maximize the reward while ensuring safety. It is an important step towards applying RL to safety-critical real-world applications. However, safe RL is challenging due to the trade-off between the two objectives [...]
Incorporating Robustness into Learning-Based Aircraft Detection and Tracking Systems
Abstract: In the field of aviation, the Detect and Avoid (DAA) problem deals with incorporating collision avoidance capabilities into current autopilot navigation systems. In order to standardize DAA capabilities, ASTM has published performance requirements to define safe DAA operations of unmanned aircraft systems (UAS). However, the performance of DAA models are entirely dependent on the [...]
Carnegie Mellon University
MSR Thesis Talk: Siddarth Venkatraman
Title: Latent Skill Models for Offline Reinforcement Learning Abstract: Offline reinforcement learning (RL) holds promise as a means to learn high-value policies from a static dataset, without the need for further environment interactions. However, a key challenge in offline RL lies in effectively stitching portions of suboptimal trajectories from the static dataset while avoiding extrapolation [...]
Long-Tailed 3D Detection via Multi-Modal Fusion
Abstract: Contemporary autonomous vehicle (AV) benchmarks have advanced techniques for training 3D detectors, particularly on large-scale LiDAR data. Surprisingly, although semantic class labels naturally follow a long-tailed distribution, these benchmarks focus on only a few common classes (e.g., pedestrian and car) and neglect many rare classes in-the-tail (e.g., debris and stroller). However, in the real [...]
MSR Thesis Talk: Eric Schneider
Title: Phenotyping and Skeletonization for Agricultural Robotics Abstract: Scientific phenotyping of plants is a crucial aspect of experimental plant breeding. By accurately measuring plant characteristics, phenotyping plays a vital role in the development of new plant varieties that are better adapted to specific environments and have improved yield, quality, and resistance to stress and disease. In [...]
MSR Thesis Talk: Shivesh Khaitan
Zoom Link: https://cmu.zoom.us/j/95273358670?pwd=Z09Jc3g1aDV1dTdTMEVUWUwxcUZPQT09 Meeting ID: 952 7335 8670 Passcode: 050721 Title: Exploring Reinforcement Learning approaches for Safety Critical EnvironmentsAbstract: Reinforcement Learning (RL) has emerged as a powerful paradigm for addressing challenging decision-making and robotic control tasks. By leveraging the principles of trial-and-error learning, RL algorithms enable agents to learn optimal strategies through interactions with an environment. However, [...]
MSR Thesis Talk: Ravi Tej Akella
Title: Distributional Distance Classifiers for Goal-Conditioned Reinforcement Learning Abstract: Autonomous systems are increasingly being deployed in stochastic real-world environments. Often, these agents are trying to find the shortest path to a commanded goal. But what does it mean to find the shortest path in stochastic environments, where every strategy has a non-zero probability of failing? At [...]
MSR Thesis Talk: Seth Karten
Title: Emergent Communication and Decision-Making in Multi-Agent Teams Abstract: Explicit communication among humans is key to coordinating and learning. In multi-agent reinforcement learning for partially-observable environments, agents may convey information to others via learned communication, allowing the team to complete its task. However, agents need to be able to communicate more than simply referential messages [...]
MSR Thesis Talk: Sashank Tirumala
Title: Tactile Sensing applied to deformable object manipulation Abstract: The application of robotic manipulation of deformable materials, such as cloth, spans various sectors including fabric manufacturing and domestic laundry management. Historically, most methodologies have employed vision-based sensors as the proprioceptive input to robot policies. However, this study aims to explore an alternate route by leveraging [...]
MSR Thesis Talk: Zhizhu Zhao
Title: Distilling View-conditioned Diffusion for 3D Reconstruction Abstract: We propose a 3D neural mode-seeking formulation that combines probabilistic generation of unseen regions with faithful reprojection of seen regions in a consistent 3D representation. Feature reprojection methods (NerFormer, PixelNeRF) are 3D consistent, but fail to hallucinate unseen regions. Image generation methods (ViewFormer) generate plausible hallucinations, but generated [...]
Differentiable Fluid-Structure Interaction for Robotics
Abstract: We present Aquarium, a differentiable fluid-structure interaction solver for robotics that offers stable simulation, accurately coupled fluid-robot physics in two dimensions, and full differentiability with respect to fluid and robot states and parameters. Aquarium achieves stable simulation with accurate flow physics by directly integrating over the incompressible Navier-Stokes equations using a fully implicit Crank-Nicolson [...]
MSR Thesis Talk: Khiem Vuong
Title: Scaling up Camera Calibration and Amodal 3D Object Reconstruction for Smart Cities Abstract: Smart cities integrate thousands of outdoor cameras to enhance urban infrastructure, but their automated analysis potential remains untapped due to various challenges. Firstly, the lack of accurate camera calibration information, such as its intrinsics parameters and external orientation, restricts the measurement [...]
From Reinforcement Learning to Robot Learning: Leveraging Prior Data and Shared Evaluation
Abstract: Unlike most machine learning applications, robotics involves physical constraints that make off-the-shelf learning challenging. Difficulties in large-scale data collection and training present a major roadblock to applying today’s data-intensive algorithms. Robot learning has an additional roadblock in evaluation: every physical space is different, making results across labs inconsistent. Two common assumptions of the robot [...]