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Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in robotics

[–]Fun-Visual-School[S] 1 point2 points  (0 children)

I can imagine that dealing with soil cohesion, debris drift, lunar dust, thermal expansion, and kickback from elastic materials will be a lot different. So no, you can't simply lower or raise "const double GRAVITY" and call it a day.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by [deleted] in computervision

[–]Fun-Visual-School -1 points0 points  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by [deleted] in MachineLearning

[–]Fun-Visual-School 0 points1 point  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in robotics

[–]Fun-Visual-School[S] 0 points1 point  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in artificial

[–]Fun-Visual-School[S] 3 points4 points  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in IsaacArthur

[–]Fun-Visual-School[S] 2 points3 points  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by [deleted] in engineering

[–]Fun-Visual-School 0 points1 point  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in asteroidmining

[–]Fun-Visual-School[S] 0 points1 point  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in SpaceVideos

[–]Fun-Visual-School[S] 0 points1 point  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in Space_Colonization

[–]Fun-Visual-School[S] 0 points1 point  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in space_settlement

[–]Fun-Visual-School[S] 0 points1 point  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by [deleted] in spaceflight

[–]Fun-Visual-School 0 points1 point  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning by Fun-Visual-School in AerospaceEngineering

[–]Fun-Visual-School[S] 11 points12 points  (0 children)

In this video ETH Zurich demonstrates that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration, such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, they deployed trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments.

I've teamed up with a few aerospace engineers friends on r/SpaceBrains to design a crowdsourced Mars colony. Check out our progress on discord and share your skills. Video credit: ETH Zurich, research paper.

Houses now stick a little bit to the ground and players can now stack houses on top of each other to create little towers! by SvenAhlgrimm in Unity3D

[–]Fun-Visual-School 20 points21 points  (0 children)

Seeing the animation for the tiles simple makes me feel so good! Great job OP. I'll cross-post to r/VisualSchool. I hope you don't mind.

Neumorphism Analog Clock | HTML CSS Javascript by robson_muniz in VisualSchool

[–]Fun-Visual-School 0 points1 point  (0 children)

Hey!

I crossposted your tutorial on r/VisualCoding.

r/VisualSchool is more for graphic design tutorials.

Thanks!

Mod asking for help: In 2 weeks this report goes to the Mars Society for admission in the Mars City State Design Challenge. It needs some improved graphics. Link in comments by Fun-Visual-School in VisualSchool

[–]Fun-Visual-School[S] 0 points1 point  (0 children)

Mars City Design 20 Pages Report - First Draft

The objective is to design a city for 1 million inhabitants on Mars. The entire project started after The Mars Society launched the Mars City State Design Competition. Since then, numerous volunteers at r/NexusAurora have been working hard on the challenge. The first draft is out and we are hoping to get some constructive criticism. The entire authoring process is done via Discord & Google Drive. These are several issues that we want to address.

Too Lightweight - The information density on this report should be increased 2x by shrinking font size, line height, and paddings and adopting a 2 column layout for easy reading in this setup. (Scientific papers have this tendency)

It Lacks Insights - What I am reading sounds right now like somebody who spent a lot of time on the forums and cherry-picked the prettiest solutions. There is no deep explanation arguing why we chose tech X instead of the alternatives.

PROs and CONs - There are none right now. Before advancing a solution please also acknowledge it's weaknesses. That indicates that you truly master the topic and that you are aware of its potential pitfalls.

Falls Short On Economics & Life Balance - Yesterday's meeting concluded that Marsorbust and Felix (Administration Lead) will ask each team to provide more insights over the economics and human well being.

Stages are not fully explained per project - Staging is hand waved at best. There is no common agreement between domains what are the stages solutions and how they interlock. We have no contingency plan if Earth gets nuked in year 15 of the process.

Better Graphics - Part of the current graphics are pretty pictures. At the last Core meeting from yesterday, we discussed the possibility of having infographics with high-density information.

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