PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Robust Off-road Wheel Odometry with Slip Estimation

NSH 4305

Abstract: Wheel odometry is not often used in state estimation for off-road vehicles due to frequent wheel slippage, varying wheel radii, and the 3D motion of the vehicle not fitting with the 2D nature of integrated wheel odometry. This paper proposes a novel 3D preintegration of wheel encoder measurements on manifold. Our method additionally estimates [...]

Special Talk
Assistant Professor
Robotics Institute,
Carnegie Mellon University

Composable Optimization for Robotic Motion Planning and Control

Newell-Simon Hall 4305

Abstract: Contact interactions are pervasive in real-world robotics tasks like manipulation and walking. However, the non-smooth dynamics associated with impacts and friction remain challenging to model, and motion planning and control algorithms that can fluently and efficiently reason about contact remain elusive. In this talk, I will share recent work from my research group that takes an “optimization-first” [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Optimal Modular Robot Design for Mobile Manipulation in Agriculture

NSH 3305

Abstract: Although agriculture is a highly mechanized industry, numerous sectors like horticulture and floriculture heavily depend on manual labor because they require safe handling of plants and produce that can only be left to humans. However, many research and commercial robots have succeeded in several challenging dexterous manipulation tasks like harvesting, pruning, and plant health [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Aligning Robot Task and Interaction Policies to Human Values

Abstract: The value alignment problem considers how robots can learn to behave in accordance with human values. Today, robot learning paradigms enable humans to provide data (e.g., preference labels or demonstrations), which the robot uses to update its behavior (e.g., reward model or policy) to be closer to the human’s values. However, the current paradigm [...]

VASC Seminar
Wolfgang Heidrich
Professor of Computer Science and Electrical and Computer Engineering
KAUST Visual Computing Center

Learned Imaging Systems

Newell-Simon Hall 4305

Abstract: Computational imaging systems are based on the joint design of optics and associated image reconstruction algorithms. Of particular interest in recent years has been the development of end-to-end learned “Deep Optics” systems that use differentiable optical simulation in combination with backpropagation to simultaneously learn optical design and deep network post-processing for applications such as hyperspectral [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Accelerating Robot Task Learning with Large Pretrained Models and Internet Data

NSH 3305

Abstract: Large pre-trained models and internet data sources are key to general and efficient robot task learning. However, learning contact-rich behaviors, semantic task constraints, and robust task planning from internet data sources remains an open challenge. This proposal seeks to make progress towards a general robot task learning system leveraging pre-trained models and internet data. [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

A Modularized Approach to Vision-based Tactile Sensor Design Using Physics-based Rendering

NSH 4305

Abstract: Touch is an essential sensing modality for making autonomous robots more dexterous and allowing them to work collaboratively with humans. In particular, the advent of vision-based tactile sensors has resulted in efforts to design them for different robotic manipulation tasks. However, this design task remains a challenging problem. This is for two reasons: first, [...]

MSR Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Towards Universal Place Recognition

3305 Newell-Simon Hall

Title: Towards Universal Place Recognition Abstract: Place Recognition is essential for achieving robust robot localization. However, current state-of-art systems remain environment/domain-specific and fragile. By leveraging insights from vision foundation models, we present AnyLoc, a universal VPR solution that performs across diverse environments without retraining or fine-tuning, significantly outperforming supervised baselines. We further introduce MultiLoc, and enable [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Enhancing Model Performance and Interpretability with Causal Inference as a Feature Selection Algorithm

NSH 1305

Abstract: Causal inference focuses on uncovering cause-effect relationships from data, diverging from conventional machine learning which primarily relies on correlation analysis. By identifying these causal relationships, causal inference improves feature selection for predictive models, leading to predictions that are more accurate, interpretable, and robust. This approach proves especially effective with interventional data, such as randomized [...]

Seminar
Andy Kilianski
Program Manager, Health Science Futures
ARPA-H

ARPA-H and America’s Health: Pursuing High-Risk/High-Reward Research to Improve Health Outcomes for All

Newell-Simon Hall 4305

Dr. Andy Kilianski will provide an overview of ARPA-H, a new U.S. government funding agency pursuing R&D for health challenges. He will review the unique niche occupied by ARPA-H within the Department of Health and Human Services and how ARPA-H is already partnering with academia and industry to transform health outcomes across the country. Discussion [...]