MSR Thesis Defense
MSR Student
Robotics Institute,
Carnegie Mellon University

Learning for Perception and Strategy: Adaptive Omnidirectional Stereo Vision and Tactical Reinforcement Learning

Newell-Simon Hall 4305

Abstract: Multi-view stereo omnidirectional distance estimation usually needs to build a cost volume with many hypothetical distance candidates. The cost volume building process is often computationally heavy considering the limited resources a mobile robot has. We propose a new geometry-informed way of distance candidates selection method which enables the use of a very small number [...]

MSR Thesis Defense
MSR Student
Robotics Institute,
Carnegie Mellon University

Online-Adaptive Self-Supervised Learning with Visual Foundation Models for Autonomous Off-Road Driving

3305 Newell-Simon Hall

Abstract: Autonomous robot navigation in off-road environments currently presents a number of challenges. The lack of structure makes it difficult to handcraft geometry-based heuristics that are robust to the diverse set of scenarios the robot might encounter. Many of the learned methods that work well in urban scenarios require massive amounts of hand-labeled data, but [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Multimodal Representations for Adaptable Robot Policies in Human-Inhabited Spaces

NSH 4305

Abstract:  Human beings sense and express themselves through multiple modalities. To capture multimodal ways of human communication, I want to build adaptable robot policies that infer task pragmatics from video and language prompts, reason about sounds and other sensors, take actions, and learn mannerisms of interacting with people and objects. Existing solutions for robot policies [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Interleaving Discrete Search and Continuous Optimization for Kinodynamic Motion Planning

NSH 4305

Abstract: Motion planning for dynamically complex robotic tasks requires explicit reasoning within constraints on velocity, acceleration, force/torque, and kinematics such as avoiding obstacles. To meet these constraints, planning algorithms must simultaneously make high-level discrete decisions and low-level continuous decisions. For example, pushing a heavy object involves making discrete decisions about contact locations and continuous decisions [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Goal-Expressive Movement for Social Navigation: Where and When to Behave Legibly

NSH 3305

Abstract: Robots often need to communicate their navigation goals to assist observers in anticipating the robot's future actions. Enabling observers to infer where a robot is going from its movements is particularly important as robots begin to share workplaces, sidewalks, and social spaces with humans. We can use legible motion, or movements that use intentional [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Eye Gaze for Intelligent Driving

NSH 4305

Abstract:  Intelligent vehicles have been proposed as one path to increasing traffic safety and reducing on-road crashes. Driving “intelligence” today takes many forms, ranging from simple blind spot occupancy or forward collision warnings to distance-aware cruise and all the way to full driving autonomy in certain situations. Primarily, these methods are outward-facing and operate on [...]

Faculty Events
Research Professor
Robotics Institute,
Carnegie Mellon University

AI-CARING

Newell-Simon Hall 4305

AI-CARING is an NSF-sponsored institute, led by Georgia Tech, whose mission is to investigate, develop and evaluate AI technologies to help older adults live independently.  The Institute focuses on providing reminders to the older adults and alerting caregivers when necessary, assisting older adults with tasks such as meal preparation, motivating them to exercise, providing conversational [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning to Perceive and Predict Everyday Interactions

NSH 1305

Abstract:  This thesis aims to build computer systems to understand everyday hand-object interactions in the physical world – both perceiving ongoing interactions in 3D space and predicting possible interactions. This ability is crucial for applications such as virtual reality, robotic manipulations, and augmented reality. The problem is inherently ill-posed due to the challenges of one-to-many [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Sensorized Soft Material Systems with Integrated Electronics and Computing

NSH 1305

Abstract: The integration of soft and multifunctional materials in emerging technologies is becoming more widespread due to their ability to enhance or improve functionality in ways not possible using typical rigid alternatives. This trend is evident in various fields. For example, wearable technologies are increasingly designed using soft materials to improve modulus compatibility with biological [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Deep Learning for Tactile Sensing: Development to Deployment

NSH 1305

Abstract: The role of sensing is widely acknowledged for robots interacting with the physical environment. However, few contemporary sensors have gained widespread use among roboticists. This thesis proposes a framework for incorporating sensors into a robot learning paradigm, from development to deployment, through the lens of ReSkin -- a versatile and scalable magnetic tactile sensor. [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning and Translating Temporal Abstractions of Behaviour across Humans and Robots

NSH 4305

Abstract: Humans are remarkably adept at learning to perform tasks by imitating other people demonstrating these tasks. Key to this is our ability to reason abstractly about the high-level strategy of the task at hand (such as the recipe of cooking a dish) and the behaviours needed to solve this task (such as the behaviour [...]