This paper discusses the process of creating and testing the haptic feedback wearable that utilizes a sweeping Light Detection and Ranging sensor. This design comes as an extension to the capstone project for electrical engineers. The design works by attaching a LiDAR sensor to a sweeping servo motor, and whenever an object is detected by the sensor, a motor will vibrate to notify the user that an object is nearby. The design incorporates four motors so that the user will have a sense of where an obstacle is coming from and be able to navigate around that obstacle. The design was tested for its accuracy in distance and angle measurement, its efficiency when it came to processing the data, and the uncertainty of the sensor due to beam spreading. Plotting the results for the distance and angle accuracy showed that the design is capable of accurate measurements. The implementation of the code was also very efficient and had no issues with latency when processing the data from the sensor. There was also uncertainty at the larger ranges for the sensor.

The last few years have marked immense growth in the development of digital twins as developers continue to devise strategies to ensure their devices replicate their physical twin’s actions in a real-time virtual environment. The complexity and predictability of these environments can be the deciding factor for adequately testing a digital twin. As of the last year, a digital twin was in development for a capstone project at Arizona State University: CIA Research Labs - Mechanical Systems in Virtual Environments. The virtual device was initially designed for a fixed environment with known ahead-of-time obstacles. Due to the fact that the device was expected only to be traversing set environments, it was unknown how it would handle being driven in an environment with more randomized and unexpected obstacles. For this paper, the device was test driven in the original and environments with various levels of randomization to see how usable and durable the digital twin is despite only being built for environments with expected object locations. The research allowed the creators of this digital twin, utilizing the results of the trial runs and the number of obstacles unsuccessfully avoided, to understand how reliable the controls of the digital twin are when only trained for fixed terrains