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My last PhD project at CMU will be presented today and tomorrow at Conference on Robot Learning as one of the Demos: SIAT (SIAT: Stretch control with Immersive AR Teleoperation) Find Vidhi Jain, Su Li and Yonatan Bisk who will be presenting this work in person. The original goal... show more

Hao Zhu

3,198 subscribers

12,458 Aufrufe • vor 1 Jahr •via X (Twitter)

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Profilbild von Hao Zhu 朱昊

Hao Zhu 朱昊vor 1 Jahr

Despite the simplicity of the design the Stretch robot, it has a much different morphology than humans, e.g. the robots' arm rotates together with the base. Controlling which is unintuitive since manipulation also requires base movement. We created an intuitive interface -- SIAT.

Profilbild von Hao Zhu 朱昊

Hao Zhu 朱昊vor 1 Jahr

Fun fact on the technical side. I started this project 2 months before my thesis defense, but ROS was just too hard for me to set up and play with. Therefore, I decided to build a new system called AAct from scratch: The design of it worth another post.

Profilbild von Hao Zhu 朱昊

Hao Zhu 朱昊vor 1 Jahr

Check out our codebase at

Profilbild von Sabeer Saeed

Sabeer Saeedvor 1 Jahr

@corl_conf @viddivj @ybisk Super Congratulations!

Profilbild von Raghav Kapoor

Raghav Kapoorvor 1 Jahr

@corl_conf @viddivj @ybisk Congratulations and amazing work @_Hao_Zhu!!

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This will unequivocally be the biggest curated event in the lifespan of my project and I’m beyond excited to share it with you EPROM PRESENTS — SYNTHEISM ROBOTICS — JULY 29TH — DENVER — MISSION BALLROOM Enter requested data at for pre-sale registration

This will unequivocally be the biggest curated event in the lifespan of my project and I’m beyond excited to share it with you EPROM PRESENTS — SYNTHEISM ROBOTICS — JULY 29TH — DENVER — MISSION BALLROOM Enter requested data at for pre-sale registration

EPROM

79,289 Aufrufe • vor 3 Jahren

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124,588 Aufrufe • vor 2 Jahren

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VaderResearch

23,055 Aufrufe • vor 11 Monaten

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Excited to finally share Generative Value Learning (GVL), my Google DeepMind project on extracting universal value functions from long-context VLMs via in-context learning! We discovered a simple method to generate zero-shot and few-shot values for 300+ robot tasks and 50+ datasets using SOTA VLMs like Gemini (Try out the demo on our website on your robot video today!) I worked a lot on leveraging foundation models as guidance for robots in my PhD, and to me, this result forges a new frontier in how we can use foundation models for robot learning, given its broad applicability independent of embodiment and task types. Quite excited about how we can build on this work as a community!

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98,090 Aufrufe • vor 1 Jahr

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No wonder they say teleoperation is dead Peking University’s DAGroup released HumanNet, a massive 1 million hour dataset of human-centric videos that turns everyday internet footage into gold for embodied AI. It’s got first-person and third-person views, super detailed actions, object interactions, tool use, and long sequences of real behavior. Everything’s cleaned up and annotated with 3D poses, SLAM tracks, and robot-ready labels. The crazy part is,Training on just 1,000 hours of their first-person videos performs as well as (or even slightly better than) 100 hours of actual robot teleop data on downstream tasks. Basically, human videos can now stand in for expensive robot data. Scaling laws for robotics just got a whole lot more realistic. Human priors + smart curation = the future of world models.

CyberRobo

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NAVIAI-I3, a more robust humanoid robot, was launched by the Zhejiang Humanoid Robotics Innovation Center. Standing 1.8 meters tall, it can run like a human and walk on various terrains. This humanoid robot appears to be primarily designed for specialized industrial tasks, such as security patrols in underground parking lots. They previously launched the lightweight bipedal NVAI-2 and a wheeled humanoid robot. The bipedal robot is used in manufacturing operations, while the wheeled humanoid robot is used for unstructured, flexible tasks such as warehouse sorting, supermarket shelving, and office cleaning. We filmed this demonstration at the World Robot Conference; you can see it in the comments section.

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LightBox Expo

26,124 Aufrufe • vor 2 Jahren

In order for robots to be deployed in the real world, performing tasks of real value, they must be reliable. Unfortunately, even more, most robotic demos work maybe 70-80% of the time at best. The way to get better reliability is to do real-world reinforcement learning: having the robot teach itself how to perform the task up to a high level of success. The key to doing this is to start with a core of expert human data, use that to train a policy then iteratively improve it, until finally finishing with on-policy reinforcement learning. Kun Lei talks through a unified framework for imitation and reinforcement learning based on PPO, which enables this improvement process. In this episode, Kun Lei explains the theory behind his reinforcement learning method and how it allowed his robot to run in a shopping mall juicing oranges for seven hours at a time, among experiments on a wide variety of tasks and embodiments. Watch episode 58 of RoboPapers now, hosted by Michael Cho - Rbt/Acc and Chris Paxton!

In order for robots to be deployed in the real world, performing tasks of real value, they must be reliable. Unfortunately, even more, most robotic demos work maybe 70-80% of the time at best. The way to get better reliability is to do real-world reinforcement learning: having the robot teach itself how to perform the task up to a high level of success. The key to doing this is to start with a core of expert human data, use that to train a policy then iteratively improve it, until finally finishing with on-policy reinforcement learning. Kun Lei talks through a unified framework for imitation and reinforcement learning based on PPO, which enables this improvement process. In this episode, Kun Lei explains the theory behind his reinforcement learning method and how it allowed his robot to run in a shopping mall juicing oranges for seven hours at a time, among experiments on a wide variety of tasks and embodiments. Watch episode 58 of RoboPapers now, hosted by Michael Cho - Rbt/Acc and Chris Paxton!

RoboPapers

18,813 Aufrufe • vor 7 Monaten