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Here is a [https://jakeread.pages.cba.mit.edu/actuators/ scatter plot] of actuators hosted at MIT
→Add wikilink to MuJoCo (MJX)
This is a build guide for getting started experimenting with your own humanoid robot.
This is incompleteand a work in progress; you can help by expanding it! '''update:''work in progress - starting with a template, plan to expand on sections :)''''' This guide is crafted for enthusiasts who are not just looking to study humanoid robotics but to actually build and experiment with their own robots.
== Building Your Humanoid Robot ==
In humanoid robotics, choosing the right components, for example, actuators and gearboxes is crucial. Folks can use planetary and cycloidal gear actuators for their precision and strength, along with Series Elastic and Quasi-Direct Drive actuators for smoother, more natural movements. Advanced designs like the [https://humanoids.wiki/w/MIT_Cheetah MIT Cheetah ] actuator push the boundaries with fast, agile movements. Projects like the SPIN initiative are also key, as they make high-quality actuator technology more accessible, helping the field evolve and improve.
== Actuators and Gearboxes ==
RMD X10: The most powerful actuator used, designed for high torque applications with excellent control features.
==== Series Elastic and Quasi-Direct Drive Actuators ====
Series Elastic Actuators (SEAs) are used in applications requiring safe and compliant human-robot interaction. They incorporate elastic elements, allowing for energy absorption and safer interactions. Quasi-Direct Drive Actuators provide a balance between the control fidelity of direct drives and the mechanical simplicity of geared systems, promoting natural and responsive movements.
Some things to consider:
The springs in SEAs are where the magic happens. Choosing the right stiffness is a balancing act between getting precise torque control and avoiding sluggish responses. Since the spring is constantly flexing, you need sensors tuned to give accurate torque measurements. Do it regularly, and you'll keep those movements smooth and predictable. You want finely-tuned control loops to make SEAs shine. A high-frequency loop can make your robot more agile in handling external forces. PID controllers are a solid starting point, or you can try out some advanced strategies.
Friction can really impact your torque control, especially in gearboxes and linkages. Using low-friction components and proper lubrication will help keep everything moving smoothly. Make sure your spring is positioned directly between the actuator and the joint. If not, your robot won’t get the full benefit of force sensing, and that precision will be lost.If your robot is doing a lot of high-impact activities, the springs can wear out. Keep an eye on them to avoid breakdowns when you least expect them. SEAs thrive on real-time feedback. Ensure your software can handle data quickly, maybe using a real-time operating system or optimized signal processing.
==== MIT Cheetah Actuator ====
==== Comprehensive Actuator Comparisons ====
The humanoid robotics community actively discusses the need for a universal platform to compare and contrast the cost and performance of commercially available actuators. This could involve developing a comprehensive database or chart detailing each actuator's cost per Newton-meter, control schemes, and RPM, providing a valuable resource for both newcomers and experienced developers.
Here is a [https://jakeread.pages.cba.mit.edu/actuators/ scatter plot] of actuators hosted at MIT
==== Custom Actuator Developments ====
[https://irisdynamics.com/products/orca-series Iris Dynamics on electric linear actuators] suggest they can match the capabilities of human muscles, making them particularly interesting for humanoid applications.
== Assembly Tips ==
====== Isaac Gym ======
[[Reinforcement Learning ]] Training: Enables parallel environments for fast policy training.
PHC Approach: Integrates AMP for real-time pose control, making it easier to teach new skills.
====== MuJoCo (MJX)======
Offers a lightweight open-source alternative, supporting maximal coordinate constraints and easier to work with. The MuJoCo_MPC repository, created by Google DeepMind, is a toolset that combines Model Predictive Control (MPC) with the [[MuJoCo]] physics engine to create real-time behavior synthesis. With the advanced MJX extension, which uses GPU acceleration, it can simulate multiple environments in parallel. One approach is to try to replicate the techniques detailed in the AMP (Adversarial Motion Priors) paper to achieve agile humanoid behavior. For example, implementing a humanoid get-up sequence, which matches what was described in the AMP research. There’s been collaboration between different projects, like Stompy, to get humanoid simulations up and running. You could try converting Gymnasium to handle the URDF (Universal Robot Description Format) file format. Although converting to MJCF (MuJoCo's XML-based format) may present some challenges, we can still get it to work and refine the motor and actuator setup. Although [[MuJoCo]] can be slower in single-environment simulations, the MJX extension and its parallel processing potential make it a solid competitor. Compared to enviroments, like NVIDIA's Isaac Gym, MuJoCo might stand out for its extensibility and rapid development. One goal could be to try recreate the walking, running, and getting-up behaviors described in the AMP paper and use them as a foundation for training robust humanoid movements in simulation.
====== VSim ======
By understanding the nuances and strengths of each simulator, developers can refine their humanoid robots effectively. Using Isaac Sim, Isaac Gym, and complementary tools, a robust simulation approach ensures smooth virtual-to-physical transferability while reducing development time and costs.
More resources are available at [https://humanoids.wiki/w/Learning_algorithms Learning Algorithms]
== Real-World Testing ==
== Advanced Customization and Community Engagement ==
=== Open Source Projects ===
Contribute to or start your own an open-source project. For instance, platforms like GitHub host numerous projects where you can collaborate with others such as K-Scale https://github.com/kscalelabs. Check out [https://humanoids.wiki/w/Stompy Stompy!]
=== Modular Design ===
Engage in modular robot design to easily swap components or aesthetics. This approach allows for extensive customization and upgrades over time.