RI Seminar
Scott Niekum
Assistant Professor & Director of the Personal Autonomous Robotics Lab (PeARL)
Department of Computer Science, University of Texas at Austin

Scaling Probabilistically Safe Learning to Robotics

Zoom

  Abstract: Before learning robots can be deployed in the real world, it is critical that probabilistic guarantees can be made about the safety and performance of such systems.  In recent years, safe reinforcement learning algorithms have enjoyed success in application areas with high-quality models and plentiful data, but robotics remains a challenging domain for [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Routing for Persistent Exploration in Dynamic Environments with Teams of Energy-Constrained Robots

Abstract: Disaster relief scenarios require rapid and persistent situational awareness to inform first-responders of safe and viable routes through a constantly shifting environment. Knowing what roads have become flooded or are suddenly obstructed by debris can significantly improve response time and ease the distribution of resources. In a sufficiently large environment, deploying and maintaining fixed [...]

VASC Seminar
Vicente Ordónez-Román
Assistant Professor
University of Virginia

Compositional Representations for Visual Recognition

Virtual VASC - https://cmu.zoom.us/j/99437689110?pwd=cWxuQkIwWlFFZEk0QkVDUVFiN0lTdz09   Abstract: Compositionality is the ability for a model to recognize a concept based on its parts or constituents. This ability is essential to use language effectively as there exists a very large combination of plausible objects, attributes, and actions in the world. We posit that visual recognition models should be [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Sparse Spatial Hashing for Dense 3D Reconstruction

Abstract: Real-world 3D data is locally dense but globally sparse. Therefore, efficient sparse data structures are an essential component of dense 3D perception for computer vision and robotics. We manifest the power of spatial hashing by two typical tasks: dense scene reconstruction and global registration. In the first task, we accelerate volumetric integration and surface [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Coordinated online multi-robot planning

Abstract: Multi-robot applications frequently seek to employ human operators to direct robot actions online because fully automated planners struggle to encode human expertise or handle the extenuating circumstances that occur during real world operations. However, it is extremely challenging for a human to direct multi-robot teams, especially online, i.e., in real-time. From entertainment to defense, [...]

RI Seminar
Robert D. Gregg IV
Associate Professor & Associate Director of Robotics
Electrical Engineering & Computer Science , University of Michigan

From kinematic to energetic design and control of wearable robots for agile human locomotion

Abstract:  Even with the help of modern prosthetic and orthotic (P&O) devices, lower-limb amputees and stroke survivors often struggle to walk in the home and community. Emerging powered P&O devices could actively assist patients to enable greater mobility, but these devices are currently designed to produce a small set of pre-defined motions. Finite state machines [...]

PhD Thesis Defense
Postdoctoral Fellow
Robotics Institute,
Carnegie Mellon University

Sensor Planning for Large Numbers of Robots

Abstract: In the wake of a natural disaster, locating and extracting victims quickly is critical because mortality rises rapidly after the first forty-eight hours. In order to assist search and rescue teams and improve response times, teams of aerial robots equipped with sensors and cameras can engage in sensing tasks such as mapping buildings, assessing [...]

VASC Seminar

Making 3D Predictions with 2D Supervision

Abstract: Building computer vision systems that understand 3D shape are important for applications including autonomous vehicles, graphics, and VR / AR. If we assume 3D shape supervision, we can now build systems that do a reasonable job at predicting 3D shapes from images. However, 3D supervision is difficult to obtain at scale; therefore we should [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

3D Multi-Object Tracking for Autonomous Driving

Abstract: 3D multi-object tracking (MOT) is a key component of a perception system for autonomous driving. Due to recent progress in 3D object detection in the context of autonomous driving, recent work in 3D MOT primarily focuses on online tracking with the use of a tracking-by-detection pipeline. In this talk, we introduce a new 3D [...]

RI Seminar
Assistant Professor
Robotics Institute,
Carnegie Mellon University

The World’s Tiniest Space Program

Abstract:  The aerospace industry has experienced a dramatic shift over the last decade: Flying a spacecraft has gone from something only national governments and large defense contractors could afford to something a small startup can accomplish on a shoestring budget. A virtuous cycle has developed where lower costs have led to more launches and the [...]