fred
blossom-public
| fred | blossom-public | |
|---|---|---|
| 4 | 1 | |
| 99 | 1 | |
| - | - | |
| 5.9 | 3.7 | |
| 6 months ago | 2 days ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
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fred
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Ask HN: Best way to learn robotics with a 10 year old?
Thanks, that's very interesting, bookmarked! I found https://github.com/thomashiemstra/fred whilst searching, which also uses dynamixel motors, but very expensive ones.
It does look very smooth motion-wise though!
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Anyone know of any good robotic arm programming simulators?
Another option: pybullet. If you just want to learn and you don't need a super high performant system go with python. As an example my code for controlling a simulated robot arm with pybullet my code
- Fred the Robot Arm – 6 DOF 3D printed dynamixel robot arm
- Obstacle avoidance using deep reinforcement learning on a 3d printed 6 DOF robot arm. Github in comments.
blossom-public
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Ask HN: Best way to learn robotics with a 10 year old?
Thanks!
There is a guide available in the repo's wiki: https://github.com/hrc2/blossom-public/wiki
Our contributors' forks and extensions may also be useful:
https://github.com/interaction-lab/blossom-public
https://github.com/interaction-lab/BlossomNav
Regarding sourcing the parts, there are online services available to order 3D-printed parts as you would a PCB. The *.stl files are available in the wiki. Though with how accessible 3D printers have become — the well-supported Ender 3 is available for under $100 at Micro Center — you may want to consider taking up printing as a family activity.
What are some alternatives?
trax - Trax — Deep Learning with Clear Code and Speed
BlossomNav - BlossomNav: A Low-Cost Software Suite for Mobile Socially Assistive Robots
blossom-public - Public Repo for the Cornell Blossom Robot
gazebo-classic - Gazebo classic. For the latest version, see https://github.com/gazebosim/gz-sim
robot-arm - Imitation learning with iPhone based teleoperation of a low-cost robot arm.
habitat-lab - A modular high-level library to train embodied AI agents across a variety of tasks and environments.