Upper limb exoskeletons (ULEs) are robotic devices that can mobilize a severely disabled individual's arm and help the user perform some activities of daily living independently. Despite advancement in the mechanical design of ULEs, a versatile control interface that enables full and continuous control of a ULE with multiple degrees of freedom for a user with disability in both arms and legs (tetraplegia) still requires further research and development. In this study, ten individuals with tetraplegia used a tongue-based interface to fully control a five degrees of freedom ULE for a drinking and a snacking task. This required moving the ULE hand from a wheelchair armrest position to grasp an object (bottle or strawberry) placed on a table in front of the participant, moving the object towards them until it touched a face shield, and placing the object on the table. All participants successfully controlled the exoskeleton and completed the tasks. The drinking task lasted 149.6 s on the first day and 122.9 s (median) on the second day of using the exoskeleton. The participants performed the snacking task only on the first day of ULE use and achieved a median task time of 167.0 s. The study showed that the tongue interface could provide effective, efficient, and safe control of the exoskeleton.

Managing road assets, such as roadside curbs, is one of the interests of municipalities. As an interesting application of computer vision, this paper proposes a system for automated measurement of the height of the roadside curbs. The developed system uses the spatial information available in the disparity image obtained from a stereo setup. Data about the geometry of the scene is extracted in the form of a row-wise histogram of the disparity map. From parameterizing the two strongest lines, each pixel can be labeled as belonging to one plane, either ground, sidewalk or curb candidates. Experimental results show that the system can measure the height of the roadside curb with good accuracy and precision.