# Conceptualization of Cloud-Based Motion Analysis and Navigation for Wearable Robotic Applications

## TL;DR

This paper introduces a cloud-based system to help wearable robots better navigate by predicting pedestrian behavior using geographical data and activity recognition.

## Contribution

A novel cloud-based system combining geographical mapping and activity recognition for wearable robotics is proposed.

## Key findings

- The system provides context about pedestrian behavior using hindsight information.
- Partial implementation and testing showed the concept is viable and extensible.

## Abstract

The behavior of pedestrians in a non-constrained environment is difficult to predict. In wearable robotics, this poses a challenge, since devices like lower-limb exoskeletons and active orthoses need to support different walking activities, including level walking and climbing stairs. While a fixed movement trajectory can be easily supported, switches between these activities are difficult to predict. Moreover, the demand for these devices is expected to rise in the years ahead. In this work, we propose a cloud software system for use in wearable robotics, based on geographical mapping techniques and Human Activity Recognition (HAR). The system aims to give context to the surrounding pedestrians by providing hindsight information. The system was partially implemented and tested. The results indicate a viable concept with great extensibility prospects.