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 [...]
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 [...]
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 [...]
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 [...]
Perceiving 3D Human-Object Spatial Arrangements from a Single Image In-the-wild
Abstract: We live in a 3D world that is dynamic—it is full of life, with inhabitants like people and animals who interact with their environment through moving their bodies. Capturing this complex world in 3D from images has a huge potential for many applications such as compelling mixed reality applications that can interact with people [...]
A future with affordable Self-driving vehicles
(Video to appear once approved) Abstract: We are on the verge of a new era in which robotics and artificial intelligence will play an important role in our daily lives. Self-driving vehicles have the potential to redefine transportation as we understand it today. Our roads will become safer and less congested, while parking spots will be repurposed as leisure [...]
Detection of Photo Manipulation with Media Forensics
Abstract: Rapid progress in machine learning, computer vision and graphics leads to successive democratization of media manipulation capabilities. While convincing photo and video manipulation used to require substantial time and skill, modern editors bring (semi-) automated tools that can be used by everyone. Some of the most recent examples include manipulation of human faces, e.g., [...]
Robotics and Biosystems
Abstract: Research at the Center for Robotics and Biosystems at Northwestern University encompasses bio-inspiration, neuromechanics, human-machine systems, and swarm robotics, among other topics. In this talk I will give an overview of some of our recent work on in-hand manipulation, robot locomotion on yielding ground, and human-robot systems. Biography: Kevin Lynch received the B.S.E. degree [...]
Advancing the State of the Art of Computer Vision for Billions of Users
Abstract: At Google, advancing the state of the art of computer vision is very impactful as there are billions of users of Google products, many of which require high-quality, artifact-free images. I will share what we learned from successfully launching core computer vision techniques for various Google products, including PhotoScan (Photos), seamless Google Street View [...]
Carnegie Mellon University
Ergodic Trajectory Optimization for Information Gathering
Abstract: Planetary robots currently rely on significant guidance from expert human operators. Science autonomy adds algorithms and methods for autonomous scientific exploration to improve efficiency of discovery and overcome limited communication bandwidth and delay bottlenecks. This research focuses on planning trajectories for information gathering and choosing sampling locations that have the most informative samples. We [...]
Learning-based 6D Object Pose Estimation in Real-world Conditions
Abstract: Estimating the 6D pose, i.e., 3D rotation and 3D translation, of objects relative to the camera from a single input image has attracted great interest in the computer vision community. Recent works typically address this task by training a deep network to predict the 6D pose given an image as input. While effective on [...]
SubT Fall Update Webinar Led by CMU’s Robotics Institute faculty members Sebastian Scherer and Matt Travers, as well as OSU’s Geoff Hollinger
We invite you to meet members of the award-winning Team Explorer, the CMU DARPA Subterranean Challenge team, and learn more about this groundbreaking competition. Some of the world's top universities have entered the DARPA Subterranean Challenge, developing technologies to map, navigate, and search underground environments. Led by CMU's Robotics Institute faculty members Sebastian Scherer and Matt [...]