Seminar
Carnegie Mellon University
Improving Multirotor Trajectory Tracking Performance using Learned Dynamics Models
Abstract: Multirotors and other aerial vehicles have recently seen a surge in popularity, partly due to a rise in industrial applications such as inspection, surveillance, exploration, package delivery, cinematography, and others. Crucial to multirotors' successes in these applications, and enabling their suitability for other applications, is the ability to accurately track trajectories at high speed [...]
Carnegie Mellon University
Automatic Real-time Anomaly Detection for Autonomous Aerial Vehicles
Abstract: The recent incidents with Boeing 737 Max 8 aircraft have raised concerns about the safety and reliability of autopilots and autonomous operations. There is a growing need for methods to monitor the status of aircraft and report any faults and anomalies to the human pilot or to the autopilot to deal with the emergency [...]
Creative Robots with Deep Reinforcement Learning
Recent advances in Deep Reinforcement Learning (DRL) algorithms provided us with the possibility of adding intelligence to robots. Recently, we have been applying a variety of DRL algorithms to the tasks that modern control theory may not be able to solve. We observed intriguing creativity from robots when they are constrained in reaching a certain [...]
Teruko Yata Memorial Lecture – Understanding Human Behavior for Robotic Assistance and Collaboration
Speaker: Henny Admoni, Assistant Professor, Robotics Institute Carnegie Mellon University Title: Understanding Human Behavior for Robotic Assistance and Collaboration . Human-robot collaboration has the potential to transform the way people work and live. Researchers are currently developing robots that assist people in public spaces, on the job, and in their homes. To be effective assistants, these robots [...]
Active Learning in Robot Motion Control
Abstract: Motion motivated by information needs can be found throughout natural systems, yet there is comparatively little work in robotics on analyzing and synthesizing motion for information. Instead, engineering analysis of robots and animal motion typically depends on defining objectives and rewards in terms of states and errors on states. This is how we formulate [...]
Event Cameras: Image Reconstruction, Convolutions and Color
Abstract: Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent timestamped spikes at local intensity changes, called ‘events’. Event cameras offer advantages over conventional frame-based cameras in terms of latency, high dynamic range (HDR) and temporal resolution. Event cameras do not output conventional image frames, thus, image reconstruction from events enables [...]
From Farm to Takeoff: Ground and Aerial Robots for Biological Systems Analysis
Abstract: Biological and agricultural environments are dynamic, unstructured, and uncertain, posing challenges for environmental data collection at the necessary spatial and temporal scales to enable meaningful systems analysis. Small unmanned systems, however, can overcome some of these challenges by enabling autonomous or human-assisted image-based and in situ environmental data collection. This talk will present a suite of [...]