Wearable assistive robotics with integrated sensing

MIT CSAIL has developed a new way to rapidly design and fabricate soft pneumatic actuators with integrated sensing. Such actuators can be used as the backbone in a variety of applications such as assistive wearables, robotics, and rehabilitative technologies. Read the technical paper at http://pneuact.csail.mit.edu/file/CHI2022.pdf YouTube Source for this AI Video

Computer Vision – Lecture 1.1 (Introduction: Organization)

Lecture: Computer Vision (Prof. Andreas Geiger, University of Tübingen) Course Website with Slides, Lecture Notes, Problems and Solutions: https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/computer-vision/ The goal of computer vision is to compute geometric and semantic properties of the three-dimensional world from digital images. Problems in this field include reconstructing the 3D shape of an object, determining how things are moving […]

MIT's Mini Cheetah robot runs faster than ever

A new method allows MIT’s Mini Cheetah to learn how to run fast and adapt to walking on challenging terrain. This learning-based method outperforms previous human-designed methods and allowed the Mini Cheetah to set a record for speed. More info: https://news.mit.edu/2022/3-questions-how-mit-mini-cheetah-learns-run-fast-0317 Visit the project page at https://sites.google.com/view/model-free-speed/ The work was supported by DARPA Machine Common […]

SingularityNET: International Women's Day Panel | #breakthebias

The theme of International Womens Day 2022 is “Break the Bias”. Join us for a panel discussion hosted by SingularityNET on how AI can be used to break the bias! Featuring: Sophia the Robot, Jasmine Smith (CEO Rejuve), Julia Chin (Head of Compliance Hugo Save SG), Meenakshi Iyer (MD, Retail T&I, Head GBS Bangelore T&I […]

Let's get physical – DeepMind: The Podcast (Season 2, Episode 4)

Do you need a body to have intelligence? And can one exist without the other? Hannah takes listeners behind the scenes of DeepMind’s robotics lab in London where she meets robots that are trying to independently learn new skills, and explores why physical intelligence is a necessary part of intelligence. Along the way, she finds […]

Trends in Deep Reinforcement Learning with Kamyar Azizzadenesheli – #560

Today we’re joined by Kamyar Azizzadenesheli, an assistant professor at Purdue University, to close out our AI Rewind 2021 series! In this conversation, we focused on all things deep reinforcement learning, starting with a general overview of the direction of the field, and though it might seem to be slowing, thats just a product of […]

Mastering Robotics with Hindsight Experience Replay | Paper Analysis

Hindisght experience replay works pretty simply: swap out the original goal your agent was trying to receive with one it actually received. It deals with environments with sparse rewards and large state spaces. Check out my analysis of the paper here. Learn how to turn deep reinforcement learning papers into code: Get instant access to […]

Introduction to TF Agents and Deep Q Learning (Reinforcement learning with TensorFlow Agents)

Wei Wei, a Developer Advocate for TensorFlow, introduces TF Agents and walks through how to use the Deep Q Learning model to solve the cartpole environment. Resources: TensorFlow Agents homepage → https://goo.gle/34i7MAI Train a Deep Q Network with TF Agents Tutorial → https://goo.gle/3oz26ZQ TF-Agent DQN example → https://goo.gle/3HxmXnM Reinforcement Learning Lecture Series 2021 (DeepMind x […]

SingularityNET: Awakening Health – The 7️⃣th installment in the SingularityNET Ecosystem update series

Blog: https://blog.singularitynet.io/awakening-health-singularitynet-ecosystem-roadmap-end-of-year-review-series-7-7019db83d70 Awakening Health Website: https://awakening.health The Awakening Health fusion of biomedical knowledge, AI and robotics is poised to drive the massive advent of healthcare robots to transform the medical arena. Grace, the world’s foremost robotic nursing assistant and elder care robot, will be the face and heart of this transformation. —- SingularityNET is a […]

Artificial Intelligence will Take Over These Jobs in 2022

Robots taking advantage of the newest advances in Artificial Intelligence systems are expected to make a huge dent in the job market of 2022 as workers are wanting higher wages and better working conditions. These robots and AI’s outcompete and outright beat humans in many fields such as translation, self driving, news article reporting and […]

SingularityNET: Agent Based Modeling of COVID-19: Next Steps and Broader Implications – Dr. Ben Goertzel

➡️ COVID-19 Simulation Summit Playlist: https://www.youtube.com/playlist?list=PLAJnaovHtaFR5puHCN4W_4o8cgIHdawDb ——————————————— 👀 About the speaker Dr. Goertzel is one of the world’s foremost experts in Artificial General Intelligence, a subfield of AI oriented toward creating thinking machines with general cognitive capability at the human level and beyond. He has decades of expertise applying AI to practical problems in areas […]

CoRL 2020, Spotlight Talk 392: MultiPoint: Cross-spectral registration of thermal and optical aer…

“**MultiPoint: Cross-spectral registration of thermal and optical aerial imagery** Florian Achermann (ETH Zurich)*; Andrey Kolobov (Microsoft); Debadeepta Dey (Microsoft); Timo Hinzmann (ETH Zürich); Jen Jen Chung (ETH Zurich); Roland Siegwart (ETH Zürich, Autonomous Systems Lab); Nicholas Lawrance (ETH Zürich) Publication: http://corlconf.github.io/paper_392/ **Abstract** While optical cameras are ubiquitous in robotics, some robots can sense the world […]

CoRL 2020, Spotlight Talk 368: Time-Bounded Mission Planning in Time-Varying Domains with Semi-MD…

**Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes** Paul Duckworth (University of Oxford)*; Bruno Lacerda (University of Oxford); Nick Hawes (Oxford Robotics Institute) Publication: http://corlconf.github.io/paper_368/ **Abstract** Uncertain, time-varying dynamic environments are ubiquitous in real world robotics. We propose an online planning framework to address time-bounded missions under time-varying dynamics, where those dynamics […]

CoRL 2020, Spotlight Talk 331: Robot Action Selection Learning via Layered Dimension Informed Pro…

“**Robot Action Selection Learning via Layered Dimension Informed Program Synthesis** Jarrett Holtz (Univ of Texas)*; Arjun Guha (Northeastern University); Joydeep Biswas (University of Texas at Austin) Publication: http://corlconf.github.io/paper_331/ **Abstract** Action selection policies (ASPs), used to compose low-level robot skills into complex high-level tasks are commonly represented as neural networks (NNs) in the state of the […]

CoRL 2020, Spotlight Talk 381: Learning Object-conditioned Exploration using Distributed Soft Act…

“**Learning Object-conditioned Exploration using Distributed Soft Actor Critic** Ayzaan Wahid (Google)*; Austin C Stone (Google); Kevin Chen (Stanford); Brian Ichter (Google Brain); Alexander Toshev (Google) Publication: http://corlconf.github.io/paper_381/ **Abstract** Object navigation is defined as navigating to an object of a given label in a complex, unexplored environment. In its general form, this problem poses several challenges […]

Aaron Ames Interview – Integrative Learning for Robotic Systems

This week on the podcast we’re featuring a series of conversations from the AWS re:Invent conference in Las Vegas. I had a great time at this event getting caught up on the latest and greatest machine learning and AI products and services announced by AWS and its partners. Today we’re joined by Aaron Ames, Professor […]

CoRL 2020, Spotlight Talk 385: Learning a natural-language to LTL executable semantic parser for …

“**Learning a natural-language to LTL executable semantic parser for grounded robotics** Christopher Wang (MIT)*; Candace Ross (Massachusetts Institute of Technology); Yen-Ling Kuo (MIT); Boris Katz (MIT); Andrei Barbu (MIT) Publication: http://corlconf.github.io/paper_385/ **Abstract** Children acquire their native language with apparent ease by observing how language is used in context and attempting to use it themselves. They […]

CoRL 2020, Spotlight Talk 45: Positive-Unlabeled Reward Learning

“**Positive-Unlabeled Reward Learning** Danfei Xu (Stanford University)*; Misha Denil (DeepMind) Publication: http://corlconf.github.io/paper_45/ **Abstract** Learning reward functions from data is a promising path towards achieving scalable Reinforcement Learning (RL) for robotics. However, a major challenge in training agents from learned reward models is that the agent can learn to exploit errors in the reward model to […]

CoRL 2020, Spotlight Talk 364: Belief-Grounded Networks for Accelerated Robot Learning under Part…

“**Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability** Hai Nguyen (Northeastern University)*; Brett Daley (Northeastern University); Xinchao Song (Northeastern University); Christopher Amato (Northeastern University); Robert Platt (Northeastern University) Publication: http://corlconf.github.io/paper_364/ **Abstract** Many important robotics problems are partially observable where a single visual or force-feedback measurement is insufficient to reconstruct the state. Standard approaches involve […]

CoRL 2020, Spotlight Talk 340: Policy learning in SE(3) action spaces

“**Policy learning in SE(3) action spaces** Dian Wang (Northeastern University)*; Colin Kohler (Northeastern); Robert Platt (Northeastern University) Publication: http://corlconf.github.io/paper_340/ **Abstract** In the spatial action representation, the action space spans the space of target poses for robot motion commands, i.e. SE(2) or SE(3). This approach has been used to solve challenging robotic manipulation problems and shows […]

CoRL 2020, Spotlight Talk 345: Amodal 3D Reconstruction for Robotic Manipulation via Stability an…

**Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity** William Agnew (University of Washington)*; Christopher Xie (University of Washington); Aaron Walsman (University of Washington); Octavian Murad (University of Washington); Yubo Wang (University of Washington); Pedro Domingos (University of Washington); Siddhartha Srinivasa (University of Washington) Publication: http://corlconf.github.io/paper_345/ **Abstract** Learning-based 3D object reconstruction enables single- or […]

CoRL 2020, Spotlight Talk 101: Modeling Long-horizon Tasks as Sequential Interaction Landscapes

“**Modeling Long-horizon Tasks as Sequential Interaction Landscapes** Soeren Pirk (Google)*; Karol Hausman (Google Brain); Alexander Toshev (Google); Mohi Khansari (X, The Moonshot Factory) Publication: http://corlconf.github.io/paper_101/ **Abstract** Task planning over long-time horizons is a challenging and open problem in robotics and its complexity grows exponentially with an increasing number of subtasks. In this paper we present […]