The article discusses the benefits and challenges of combining Blender and Nvidia Isaac Sim to create realistic simulations for robotics applications. By integrating Blender’s 3D modeling and animation capabilities with Nvidia Isaac Sim’s simulation software, more detailed and accurate models can be developed for testing and refining algorithms. Additionally, synthetic data generated from Nvidia Isaac Sim can be used to train deep perception models, which reduces the time and effort required to gather and annotate datasets.

This blog is the second part of a two-part series where we will introduce the usage of sensor fusion in Autonomous Mobile Robots (AMRs) that are enabled to work with ROS (Robot Operating System) 2. In the first part, we introduced sensor fusion, briefly covered a sensor fusion algorithm called EKF (Extended Kalman Filters), and then walked through some of the experiments we did in simulation and on our AMR.