Robohub.org
 

What is the best simulation tool for robotics?


by
20 July 2021



share this:

What is the best simulation tool for robotics? This is a hard question to answer because many people (or their companies) specialize in one tool or another. Some simulators are better at one aspect of robotics than at others. When I’m asked to recommend the best simulation tool for robotics I have to find an expert and hope that they are current and across a wide range of simulation tools in order to give me the best advice, which was why I took particular note of the recent review paper from Australia’s CSIRO, “A Review of Physics Simulators for Robotics Applications” by Jack Collins, Shelvin Chand, Anthony Vanderkop, and David Howard, published in IEEE Access (Volume: 9).

“We have compiled a broad review of physics simulators for use within the major fields of robotics research. More specifically, we navigate through key sub-domains and discuss the features, benefits, applications and use-cases of the different simulators categorised by the respective research communities. Our review provides an extensive index of the leading physics simulators applicable to robotics researchers and aims to assist them in choosing the best simulator for their use case.”

Simulation underpins robotics because it’s cheaper, faster and more robust than real robots. While there are some guides that benchmark simulators against real world tasks there isn’t a comprehensive review. A more thorough review can address gaps and needs in research and research challenges for simulation. The authors focus on seven sub-domains: Mobile Ground Robotics; Manipulation; Medical Robotics; Marine Robotics; Aerial Robotics; Soft Robotics and Learning for Robotics.

I’m going to cut to the chase and provide a copy of the final comparison tables of each sub-domain but for anyone interested in utilizing these recommendations, then I recommend reading the rationale behind the rankings in the full review article. The authors also consider whether or not a simulator is actively supported. Handy to know! And the paper is also an excellent source of information about various historic and current robotics competitions.

Mobile Ground Robotics:

TABLE 1 Feature Comparison Between Popular Robotics Simulators

TABLE 1 Feature Comparison Between Popular Robotics Simulators

TABLE 2 Feature Comparison Between Popular Robotics Simulators Used for Mobile Ground Robotics

TABLE 2 Feature Comparison Between Popular Robotics Simulators Used for Mobile Ground Robotics

Manipulation:

TABLE 3 Feature Comparison for Popular Robotics Simulators Used for Manipulation

TABLE 3 Feature Comparison for Popular Robotics Simulators Used for Manipulation

Medical Robotics:

TABLE 4 Feature Comparison of Popular Robotics Simulators Used for Medical Robotics

TABLE 4 Feature Comparison of Popular Robotics Simulators Used for Medical Robotics

Marine Robotics:

TABLE 5 Feature Comparison of Popular Simulators Used for Marine Robotics

TABLE 5 Feature Comparison of Popular Simulators Used for Marine Robotics

Aerial Robotics:

TABLE 6 Feature Comparison of Popular Simulators Used for Aerial Robotics

TABLE 6 Feature Comparison of Popular Simulators Used for Aerial Robotics

Soft Robotics:

TABLE 7 Feature Comparison of Popular Simulators Used for Soft Robotics

TABLE 7 Feature Comparison of Popular Simulators Used for Soft Robotics

Learning for Robotics:

TABLE 8 Feature Comparison of Popular Simulators Used in Learning for Robotics

Conclusions:

As robotics makes more use of deep learning, simulators that can deal with data on the fly become necessary, and also a potential solution for simulation problems regarding points of contact or collisions. Rather than utilize multiple simulation methods to make a clearer abstraction of the real world in these boundary situations, the answer may be to insert neural networks trained to replicate the properties of difficult phenomena into the simulator. There is further discussion on differentiable simulation, levels of abstraction and the expansion of libraries, plug-ins, toolsets, benchmarking and algorithmic integration, all increasing both the utility and complexity of simulation for robotics.

As the field of simulation for robotics grows, so does the need for metrics that capture the accuracy of the real world representation.  “Finally, we predict that we will see further research into estimating and modeling uncertainty of simulators.”

This may have been the first review article on simulation for robotics but hopefully not the last. There’s a clear need to study and measure the field. I found the sections on soft robotics and learning for robotics particularly interesting, as the paper discussed the difficulties of simulation in these fields. And please attribute any errors in this summary to my mistakes. Read the full review here: https://ieeexplore.ieee.org/document/9386154

Published in: IEEE Access ( Volume: 9)
Page(s): 51416 – 51431
Date of Publication: 25 March 2021 
Electronic ISSN: 2169-3536
Publisher: IEEE
Funding Agency:
CCBY – IEEE is not the copyright holder of this material. Please follow the instructions via https://creativecommons.org/licenses/by/4.0/ to obtain full-text articles and stipulations in the API documentation.


tags:


Silicon Valley Robotics is an industry association supporting innovation and commercialization of robotics technologies.
Silicon Valley Robotics is an industry association supporting innovation and commercialization of robotics technologies.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Wristband enables wearers to control a robotic hand with their own movements

  13 Jul 2026
By moving their hands and fingers, users can direct a robot to play the piano, shoot a basketball, or manipulate objects in a virtual environment.

#RoboCup2026 social media round-up

  08 Jul 2026
Find out what the teams got up to at this year's RoboCup extravaganza in Incheon.

#RoboCup2026 – humanoid league knockout stages

  06 Jul 2026
Find out who won the small, middle and large divisions in Incheon.

#RoboCup2026 – humanoid league day 2

  03 Jul 2026
Find out the latest from day two of the competition.

Reflections from ICRA 2026

  02 Jul 2026
From dancing robots to moral machines: our Assistant Editor reflects on ICRA 2026.

#RoboCup2026 – humanoid league day 1

  02 Jul 2026
In the first of our round-ups from the humanoid league we introduce the competition, and report some preliminary results.

What’s coming up at #RoboCup2026?

  29 Jun 2026
Find out what's in store at this year's international competition.

Robot Talk Episode 162 – The robot doctor will see you now

  26 Jun 2026
In this special live recording at the Great Exhibition Road Festival in London, Claire chatted to George Mylonas (Imperial College London), Antonia Tzemanaki (University of Bristol) and Tom Vercauteren (King’s College London) about robotics and AI in medicine and healthcare.



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence