RI Seminar

Abstract: Despite the incredible capabilities (speed and repeatability) of our hardware today, many robot manipulators are deliberately programmed to avoid dynamics – moving slow enough so they can adhere to quasi-static assumptions of the world. In contrast, people frequently (and subconsciously) make use of dynamic phenomena to manipulate everyday objects – from unfurling blankets, to [...]

Abstract: The rapid evolution of ubiquitous sensing, communication, and computation technologies has revolutionized of cyber-physical systems (CPS) across virous domains like robotics, smart grids, aerospace, and smart cities. Integrating learning into dynamic systems control presents significant Embodied AI opportunities. However, current decision-making frameworks lack comprehensive understanding of the tridirectional relationship among communication, learning and control, [...]

Abstract: Data efficiency, i.e., learning from small datasets, is of practical importance in many real-world applications and decision-making systems. Data efficiency can be achieved in multiple ways, such as probabilistic modeling, where models and predictions are equipped with meaningful uncertainty estimates, transfer learning, or the incorporation of valuable prior knowledge. In this talk, I will [...]

Abstract: The seminar will review a series of robotic systems built at the Johnson Space Center over the last 20 years. These will include wearable robots (exoskeletons, powered gloves and jetpacks), manipulation systems (ISS cranes down to human scale) and lunar mobility systems (human surface mobility and robotic rovers). As all robotics presentations should, this [...]

Abstract:  The growing power in computing and AI promises a near-term future of human-machine teamwork. In this talk, I will present my research group’s efforts in understanding the complex dynamics of human-machine interaction and designing intelligent machines aimed to assist and collaborate with people. I will focus on 1) tools for onboarding machine teammates and [...]

Abstract: Robot manipulation of rigid household objects and environments has made massive strides in the past few years due to the achievements in computer vision and reinforcement learning communities. One area that has taken off at a slower pace is in manipulating deformable objects. For example, surgical robotics are used today via teleoperation from a [...]

Abstract: The performance of an AI is nearly always associated with the amount of data you have at your disposal. Self-supervised machine learning can help – mitigating tedious human supervision – but the need for massive training datasets in modern AI seems unquenchable. Sometimes it is not the amount of data, but the mismatch of [...]

Abstract: For robots to be able to truly integrate human-populated, dynamic, and unpredictable environments, they will have to have strong adaptive capabilities. In this talk, I argue that these adaptive capabilities should leverage interaction with end users, who know how (they want) a robot to act in that environment. I will present an overview of [...]

Abstract:  Data, especially large-scale labeled data, has been a critical driver of progress in computer vision. However, many important tasks remain starved of high-quality data. Synthetic data from computer graphics is a promising solution to this challenge, but still remains in limited use. This talk will present our work on Infinigen, a procedural synthetic data [...]

Abstract: As humanity returns to the Moon and is developing outposts and related infrastructure, we need to understand how robots and work machines will behave in this harsh environment. It is challenging to find representative testing environments on Earth for Lunar and planetary rovers. To investigate the effects of reduced-gravity on interactions with granular terrains, [...]