Drake: Model-Based Design and Verification for Robotics
Model-Based Design and Verification for Robotics A C++ / Python toolbox supported by the Toyota Research Institute. Install Learn More Core Library Modeling Dynamical Systems APITUTORIAL Solving Mathematical Programs APITUTORIAL Multibody Kinematics and Dynamics APITUTOR
Before you start
- Basic Python familiarity
- Comfort with algebra or calculus basics
- Interest in robotics systems
About this guide
Model-Based Design and Verification for Robotics
A C++ / Python toolbox supported by the Toyota Research Institute.
Install Learn More
Core Library
Modeling Dynamical Systems
APITUTORIAL
Solving Mathematical Programs
APITUTORIAL
Multibody Kinematics and Dynamics
APITUTORIAL
Overview [...] You can read more about the vision for Drake in this blog post.
We hope you find this tool useful. Please see Getting Help if you wish to share your comments, questions, succes
Common questions
What will I learn in Drake: Model-Based Design and Verification for Robotics?
Model-Based Design and Verification for Robotics A C++ / Python toolbox supported by the Toyota Research Institute. Install Learn More Core Library Modeling Dynamical Systems APITUTORIAL Solving Mathematical Programs APITUTORIAL Multibody Kinematics and Dynamics APITUTOR
Is Drake: Model-Based Design and Verification for Robotics free?
HumanoidHub has not verified public pricing for this guide. Open MIT OpenCourseWare for the current access terms before enrolling.
Do I need any prerequisites?
Recommended prep: Basic Python familiarity; Comfort with algebra or calculus basics; Interest in robotics systems.
How long does it take?
Self-paced (provider defined). Most learners complete this guide in self-directed sessions over a few weeks.
Does it offer a certificate?
This guide does not include a formal certificate. Focus is on the learning material itself.
Related guides
A new model offers robots precise pick-and-place solutions
SimPLE (Simulation to Pick Localize and placE), a new model developed by MIT researchers, learns to pick, regrasp and place objects using object’s computer-aided design (CAD) model
Industrial Robotics
Image 3Preview this course # Industrial Robotics Mathematical models and practical applications Created byFabrizio Frigeni Last updated 9/2019 English Image 4Preview this course Purchase options Subscribe and save From$13.00/month Access to 28,000+ top-rated courses Cancel anytime
Machine Learning | Blog Archives | Page 6 Of 6 | Udacity
Udacity transforms talent and changes lives through digital upskilling. Learn to overcome digital talent gaps with our resources on Machine Learning
Expanding on Tutorials | MIT Learn
<p>Kyle Keane talks about the logistics and purpose of expanding on tutorials, and how this is related to creating, inventing, and learning.
Helping robots practice skills independently to adapt to unfamiliar environments
A robot rapidly specializes its skills using parameter policy learning, where the machine can rapidly specialize at specific, smaller actions within a long-horizon task. The MIT CSAIL algorithm enables autonomous practice to improve at mobile-manipulation activities.
Home | Stanford HAI
Advancing AI research, education, and policy to improve the human condition.
Robots that use these skills
NEURA 4NE1
NEURA Robotics
NEURA 4NE1 is a full-size humanoid robot platform from NEURA Robotics aimed at industrial and logistics tasks, with NVIDIA Thor compute and a reservation-based rollout.
Figure 01
Figure AI
Figure 01 is Figure AI’s first humanoid robot prototype for general-purpose labor in indoor commercial and industrial spaces.
.jpg)
Hubo (KHR-2 based platform)
HUBO
HUBO (KHR-2 based) is a full-size biped humanoid research platform developed at KAIST. It is reported at 41 DOF, ~125 cm tall, and ~55 kg.
Refer a learner and get early access to our paid pathways and 1:1 mentorship pilot.
Join referral list