Sistema de detecção e modelagem de rampas e degraus para um exoesqueleto de membros inferiores

Abstract

In recent years, many studies have been carried out on the topic of exoskeletons related to locomotion assistance. The main goal of these devices is to assist the elderly and physically challenged persons in daily activities, replacing or increasing the movement of body articulations. Although significant progress has been achieved, many challenges still remain. A desirable feature for exoskeletons is the planning of autonomous movements, so that the movements are automatically adapted according to the environment that the user is facing. Therefore, it is indispensable the use of a computer vision system to provide information about the environment where the user is located, classifying the structures of the scene as walkable or not. In this sense, we propose a new strategy for ramp and step detection which are in accordance with technical standards and can be climbed for exoskeleton users. Initially, we use a RGB-D sensor to acquire depth information of the environment. Next, we perform plane segmentation using a hypothesis and verification methodology. Through the plane normal analysis, it is possible to establish ramps and steps candidates. Finally, plane dimensions are verified in order to decide whether the ramps and steps are qualified to be climbed. Results were obtained applying the method considering different environments, where it was possible to detect and model ramps and steps satisfactorily for the presented scenarios.