RI Seminar
Resilient Exploration in SubT Environments: Team Explorer’s Approach and Lessons Learned in the Final Event
Abstract: Subterranean robot exploration is difficult with many mobility, communications, and navigation challenges that require an approach with a diverse set of systems, and reliable autonomy. While prior work has demonstrated partial successes in addressing the problem, here we convey a comprehensive approach to address the problem of subterranean exploration in a wide range of [...]
Towards Robust Human-Robot Interaction: A Quality Diversity Approach
Abstract: The growth of scale and complexity of interactions between humans and robots highlights the need for new computational methods to automatically evaluate novel algorithms and applications. Exploring the diverse scenarios of interaction between humans and robots in simulation can improve understanding of complex human-robot interaction systems and avoid potentially costly failures in real-world settings. [...]
Lessons from the Field: Deep Learning and Machine Perception for field robots
Abstract: Mobile robots now deliver vast amounts of sensor data from large unstructured environments. In attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine learning techniques to mobile robotic perception. [...]
Distributed Dissipativity: Applying Foundational Stability Theory to Modern Networked Control
Abstract: Despite its diverse areas of application, the desire to optimize performance and guarantee acceptable behaviour in the face of inevitable uncertainty is pervasive throughout control theory. This creates a fundamental challenge since the necessity of robustly stable control schemes often favors conservative designs, while the desire to optimize performance typically demands the opposite. While [...]
Haptic Perspective-taking from Vision and Force
Abstract: Physically collaborative robots present an opportunity to positively impact society across many domains. However, robots currently lack the ability to infer how their actions physically affect people. This is especially true for robotic caregiving tasks that involve manipulating deformable cloth around the human body, such as dressing and bathing assistance. In this talk, I [...]
Perception-Action Synergy in Uncertain Environments
Abstract: Many robotic applications require a robot to operate in an environment with unknowns or uncertainty, at least initially, before it gathers enough information about the environment. In such a case, a robot must rely on sensing and perception to feel its way around. Moreover, it has to couple sensing/perception and motion synergistically in real [...]
Designing Robotic Systems with Collective Embodied Intelligence
Abstract: Natural swarms exhibit sophisticated colony-level behaviors with remarkable scalability and error tolerance. Their evolutionary success stems from more than just intelligent individuals, it hinges on their morphology, their physical interactions, and the way they shape and leverage their environment. Mound-building termites, for instance, are believed to use their own body as a template for [...]
Snakes & Spiders, Robots & Geometry
Abstract: Locomotion and perception are a common thread between robotics and biology. Understanding these phenomena at a mechanical level involves nonlinear dynamics and the coordination of many degrees of freedom. In this talk, I will discuss geometric approaches to organizing this information in two problem domains: Undulatory locomotion of snakes and swimmers, and vibration propagation [...]
Robotic Cave Exploration for Search, Science, and Survey
Abstract: Robotic cave exploration has the potential to create significant societal impact through facilitating search and rescue, in the fight against antibiotic resistance (science), and via mapping (survey). But many state-of-the-art approaches for active perception and autonomy in subterranean environments rely on disparate perceptual pipelines (e.g., pose estimation, occupancy modeling, hazard detection) that process the same underlying sensor data in different [...]
Safe and Stable Learning for Agile Robots without Reinforcement Learning
Abstract: My research group (https://aerospacerobotics.caltech.edu/) is working to systematically leverage AI and Machine Learning techniques towards achieving safe and stable autonomy of safety-critical robotic systems, such as robot swarms and autonomous flying cars. Another example is LEONARDO, the world's first bipedal robot that can walk, fly, slackline, and skateboard. Stability and safety are often research problems [...]
Towards $1 robots
Abstract: Robots are pretty great -- they can make some hard tasks easy, some dangerous tasks safe, or some unthinkable tasks possible. And they're just plain fun to boot. But how many robots have you interacted with recently? And where do you think that puts you compared to the rest of the world's people? In [...]
What (else) can you do with a robotics degree?
Abstract: In 2004, half-way through my robotics Ph.D., I had a panic-inducing thought: What if I don’t want to build robots for the rest of my life? What can I do with this degree?! Nearly twenty years later, I have some answers: tackle climate change in Latin America, educate Congress about autonomous vehicles, improve how [...]
Robots Should Reduce, Reuse, and Recycle
Abstract: Despite numerous successes in deep robotic learning over the past decade, the generalization and versatility of robots across environments and tasks has remained a major challenge. This is because much of reinforcement and imitation learning research trains agents from scratch in a single or a few environments, training special-purpose policies from special-purpose datasets. In [...]
Machine Learning and Model Predictive Control for Adaptive Robotic Systems
Abstract: In this talk I will discuss several different ways in which ideas from machine learning and model predictive control (MPC) can be combined to build intelligent, adaptive robotic systems. I’ll begin by showing how to learn models for MPC that perform well on a given control task. Next, I’ll introduce an online learning perspective on [...]
Learning Representations for Interactive Robotics
In this talk, I will be discussing the role of learning representations for robots that interact with humans and robots that interactively learn from humans through a few different vignettes. I will first discuss how bounded rationality of humans guided us towards developing learned latent action spaces for shared autonomy. It turns out this “bounded rationality” is not a [...]
Motion Planning Around Obstacles with Graphs of Convex Sets
Abstract: In this talk, I'll describe a new approach to planning that strongly leverages both continuous and discrete/combinatorial optimization. The framework is fairly general, but I will focus on a particular application of the framework to planning continuous curves around obstacles. Traditionally, these sort of motion planning problems have either been solved by trajectory optimization [...]
RE2 Robotics: from RI spinout to Acquisition
Abstract: It was July 2001. Jorgen Pedersen founded RE2 Robotics. It was supposed to be a temporary venture while he figured out his next career move. But the journey took an unexpected course. RE2 became a leading developer of mobile manipulation systems. Fast forward to 2022, RE2 Robotics exited via an acquisition to Sarcos Technology and [...]
Understanding the Physical World from Images
If I show you a photo of a place you have never been to, you can easily imagine what you could do in that picture. Your understanding goes from the surfaces you see to the ones you know are there but cannot see, and can even include reasoning about how interaction would change the scene. [...]
A Constructivist’s Guide to Robot Learning
Over the last decade, a variety of paradigms have sought to teach robots complex and dexterous behaviors in real-world environments. On one end of the spectrum we have nativist approaches that bake in fundamental human knowledge through physics models, simulators and knowledge graphs. While on the other end of the spectrum we have tabula-rasa approaches [...]
Next-Generation Robot Perception: Hierarchical Representations, Certifiable Algorithms, and Self-Supervised Learning
Spatial perception —the robot’s ability to sense and understand the surrounding environment— is a key enabler for robot navigation, manipulation, and human-robot interaction. Recent advances in perception algorithms and systems have enabled robots to create large-scale geometric maps of unknown environments and detect objects of interest. Despite these advances, a large gap still separates robot [...]
Structures and Environments for Generalist Agents
Abstract: We are entering an era of highly general AI, enabled by supervised models of the Internet. However, it remains an open question how intelligence emerged in the first place, before there was an Internet to imitate. Understanding the emergence of skillful behavior, without expert data to imitate, has been a longstanding goal of reinforcement [...]
Mars Robots and Robotics at NASA JPL
Abstract: In this seminar I’ll discuss Mars robots, the unprecedented results we’re seeing with the latest Mars mission, and how we got here. Perseverance’s manipulation and sampling systems have collected samples from unique locations at twice the rate of any prior mission. 88% of all driving has been autonomous. This has enabled the mission to [...]
Special RI Seminar
Title: Testing, Analysis, and Specification for Robust and Reliable Robot Software Abstract: Building robust and reliable robotic software is an inherently challenging feat that requires substantial expertise across a variety of disciplines. Despite that, writing robot software has never been easier thanks to software frameworks such as ROS: At its best, ROS allows newcomers to assemble simple, [...]
Transforming Hollywood Visual Effects with Graphics and Vision
Abstract: Paul will describe his path to developing visual effects technology used in hundreds of movies, including The Matrix, Spider-Man 2, Benjamin Button, Avatar, Maleficent, Furious 7, and Blade Runner: 2049. These techniques include image-based modeling and rendering, high dynamic range imaging, image-based lighting, and high-resolution facial scanning for photoreal digital actors. Paul will also [...]
Learning Meets Gravity: Robots that Learn to Embrace Dynamics from Data
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 [...]
Learning and Control for Safety, Efficiency, and Resiliency of Embodied AI
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, [...]
Data-Efficient Learning for Robotics and Reinforcement Learning
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 [...]
Robots at the Johnson Space Center and Future Plans
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 [...]
Becoming Teammates: Designing Assistive, Collaborative Machines
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 [...]
Teaching a Robot to Perform Surgery: From 3D Image Understanding to Deformable Manipulation
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 [...]
Learning with Less
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 [...]
Why We Should Build Robot Apprentices And Why We Shouldn’t Do It Alone
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 [...]
Toward an ImageNet Moment for Synthetic Data
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 [...]
Reduced-Gravity Flights and Field Testing for Lunar and Planetary Rovers
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, [...]
Where’s RobotGPT?
Abstract: The last years have seen astonishing progress in the capabilities of generative AI techniques, particularly in the areas of language and visual understanding and generation. Key to the success of these models are the use of image and text data sets of unprecedented scale along with models that are able to digest such large [...]
Robot Learning by Understanding Egocentric Videos
Abstract: True gains of machine learning in AI sub-fields such as computer vision and natural language processing have come about from the use of large-scale diverse datasets for learning. In this talk, I will discuss how we can leverage large-scale diverse data in the form of egocentric videos (first-person videos of humans conducting different tasks) [...]
What Makes Learning to Control Easy or Hard?
Abstract: Designing autonomous systems that are simultaneously high-performing, adaptive, and provably safe remains an open problem. In this talk, we will argue that in order to meet this goal, new theoretical and algorithmic tools are needed that blend the stability, robustness, and safety guarantees of robust control with the flexibility, adaptability, and performance of machine [...]
Soft Wearable Haptic Devices for Ubiquitous Communication
Abstract: Haptic devices allow touch-based information transfer between humans and intelligent systems, enabling communication in a salient but private manner that frees other sensory channels. For such devices to become ubiquitous, their physical and computational aspects must be intuitive and unobtrusive. The amount of information that can be transmitted through touch is limited in large [...]