OpenRDW

A Redirected Walking Library and Benchmark with Multi-User, Learning-based Functionalities and State-of-the-art Algorithms

OpenRDW extends the original Redirected Walking Toolkit and implements more new features.

The OpenRDW library provides APIs to access the attributes of scenes, to customize the RDW controllers, to simulate and visualize the navigation process, to export multiple formats of the results, and to evaluate RDW techniques. It also supports the deployment of multi-user real walking, as well as reinforcement learning-based models exported from TensorFlow or PyTorch.

The OpenRDW benchmark includes multiple testing conditions, such as walking in size varied tracking spaces or shape varied tracking spaces with obstacles, multiple user walking, etc. It also contains several classic and state-of-the-art RDW techniques, which include the above mentioned functionalities. Also, procedurally generated paths and walking paths collected from user experiments are provided for a comprehensive evaluation.

You can get more information from OpenRDW wiki.