This project focuses on implementing and validating a simple, general, and expandable pipeline for object manipulation. It is implemented as a modular framework that uses 5 configurable modules: camera controller, object detection, object segmentation, grasp proposal, and an executor (arm controller). In the current version, SUMBA implements some of the most widely used methods for each module, and the user can choose any combination of them or implement their own. These solutions are evaluated on a real robot with objects from the YCB Object and Model Set, in a tabletop manipulation task. The best results were obtained by using YOLOv8 both for object detection and segmentation.

Parkinson's Disease (PD) is a neurological disorder characterized by tremors, difficulty in movement, gait and coordination. Among other symptoms, most patients suffer from Freezing of Gait (FOG): an abrupt halt in gait, usually described by patients as “feet get glued to the ground”. Research has shown that cueing techniques help improve the patient's gait and reduce the number and duration of FOG episodes. Cueing can be defined as using external stimuli which provide temporal or spatial information to facilitate movement initiation and continuation. Although visual stimuli help alleviate FOG, state-of-the-art devices only help with scaling the gait and do not consider other known FOG triggers, such as changes in direction. Our solution (ARFoG) uses a stereo camera and state-of-the-art robotics software to dynamically build a map of the environment, localize the patient and plan trajectories to where they want to go. Once a destination is chosen via voice commands, lines indicating where to step throughout the entire trajectory are shown using Smart Glasses. With this device, the patient's focus is only on the gait movement, avoiding distractions that may trigger FoG episodes.