Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
CoppeliaSim, created by Coppelia Robotics, stands out as a dynamic and robust platform for robot simulation, effectively serving various purposes such as rapid algorithm development, factory automation modeling, quick prototyping, verification processes, educational applications in robotics, remote monitoring capabilities, safety checks, and the creation of digital twins. Its architecture supports distributed control, allowing for individual management of objects and models through embedded scripts in Python or Lua, plugins written in C/C++, and remote API clients that support multiple programming languages including Java, MATLAB, Octave, C, C++, and Rust, as well as tailored solutions. The simulator is compatible with five different physics engines—MuJoCo, Bullet Physics, ODE, Newton, and Vortex Dynamics—enabling swift and customizable dynamics calculations that facilitate highly realistic simulations of physical phenomena and interactions, such as collision responses, grasping mechanisms, and the behavior of soft bodies, strings, ropes, and fabrics. Additionally, CoppeliaSim offers both forward and inverse kinematics computations for a diverse range of mechanical systems, enhancing its utility in various robotics applications. This flexibility and capability make CoppeliaSim an essential tool for researchers and professionals in the field of robotics.
Description
NVIDIA Modulus is an advanced neural network framework that integrates the principles of physics, represented through governing partial differential equations (PDEs), with data to create accurate, parameterized surrogate models that operate with near-instantaneous latency. This framework is ideal for those venturing into AI-enhanced physics challenges or for those crafting digital twin models to navigate intricate non-linear, multi-physics systems, offering robust support throughout the process. It provides essential components for constructing physics-based machine learning surrogate models that effectively merge physics principles with data insights. Its versatility ensures applicability across various fields, including engineering simulations and life sciences, while accommodating both forward simulations and inverse/data assimilation tasks. Furthermore, NVIDIA Modulus enables parameterized representations of systems that can tackle multiple scenarios in real time, allowing users to train offline once and subsequently perform real-time inference repeatedly. As such, it empowers researchers and engineers to explore innovative solutions across a spectrum of complex problems with unprecedented efficiency.
API Access
Has API
No
API Access
Has API
No
Integrations
C
Yes
C++
Yes
Java
Yes
Lua
Yes
MATLAB
Yes
Octave
Yes
Python
Yes
Rust
Yes
Integrations
C
No
C++
No
Java
No
Lua
No
MATLAB
No
Octave
No
Python
No
Rust
No
Pricing Details
$2,380 per year
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Coppelia Robotics
Country
Switzerland
Website
www.coppeliarobotics.com
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/modulus