A Comparison of Humanoid Robot Simulators: A Quantitative Approach

by   Angel Ayala, et al.

Research on humanoid robotic systems involves a considerable amount of computational resources, not only for the involved design but also for its development and subsequent implementation. For robotic systems to be implemented in real-world scenarios, in several situations, it is preferred to develop and test them under controlled environments in order to reduce the risk of errors and unexpected behavior. In this regard, a more accessible and efficient alternative is to implement the environment using robotic simulation tools. This paper presents a quantitative comparison of Gazebo, Webots, and V-REP, three simulators widely used by the research community to develop robotic systems. To compare the performance of these three simulators, elements such as CPU, memory footprint, and disk access are used to measure and compare them to each other. In order to measure the use of resources, each simulator executes 20 times a robotic scenario composed by a NAO robot that must navigate to a goal position avoiding a specific obstacle. In general terms, our results show that Webots is the simulator with the lowest use of resources, followed by V-REP, which has advantages over Gazebo, mainly because of the CPU use.



page 4


Robotic Navigation using Entropy-Based Exploration

Robotic navigation concerns the task in which a robot should be able to ...

The Pluggable Distributed Resource Allocator (PDRA): a Middleware for Distributed Computing in Mobile Robotic Networks

We present the Pluggable Distributed Resource Allocator (PDRA), a middle...

Off Environment Evaluation Using Convex Risk Minimization

Applying reinforcement learning (RL) methods on robots typically involve...

Expressivity in Natural and Artificial Systems

Roboticists are trying to replicate animal behavior in artificial system...

A Comparative Study of Bug Algorithms for Robot Navigation

This paper presents a literature survey and a comparative study of Bug A...

Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario

Robotic systems are more present in our society every day. In human-robo...

Robotic frameworks, architectures and middleware comparison

Nowadays, the construction of a complex robotic system requires a high l...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.