## 1 Introduction  
The use of robotics for aiding people in everyday life is becoming increasingly more common and assistive robotics is a promising aspect for individuals who would otherwise be dependent on a caregiver for daily activities [1, 2]. This potential for assistive robots is especially high for individuals who are exceedingly dependent on caregivers in everyday life such as individuals with tetralegia, i.e., partial or complete loss of control in both arms and legs. A typical cause of tetralegia is SCI (spinal cord injury), and it is estimated that 250,000 to 500,000 people suffer from SCI every year [3], with roughly one-third of these cases resulting in tetralegia [4].  
The mean age of individuals with tetralegia was reported to be 33 years old when sustaining the injury [4], but especially males aged 20-29 years and females aged 15-19 years have seen spikes in the incident rate of traumatic spinal cord injuries [3]. The motivation for focusing on tetralegia is further supported by a high life expectancy after the injury, especially for young individuals [3]. An individual with tetralegia caused by SCI at the age of 25 years can often expect to live for another 40 years. One of the most important tools for individuals with tetraplegia is often a powered wheelchair, offering both mobility and independence [3]. However, tasks requiring interaction with an object, such as drinking and eating, still require assistance from a caregiver. The frustration of not being able to perform these things independently becomes even greater for prolonged sessions, for instance, during recreational activities, such as watching a movie while enjoying a beverage or snacking [5].  
To mitigate the challenges above and increase the independence of individuals with tetraplegia, we propose the novel combination of using a tongue-based interface combined with computer vision in a semi-autonomous control scheme to enable individuals with tetraplegia to effectively control an upper limb exoskeleton, as shown in Figure 1.  
An upper limb exoskeleton is used, as several studies have successfully demonstrated how it can help restore some of the lost functionality for individuals with movement impairments in the arms [6; 7]. Furthermore, the tongue-based interface has previously been shown to be an efficient and suitable interface for individuals with tetraplegia to control an exoskeleton [8; 9]. Finally, a semi-autonomous control scheme assists the user in controlling the exoskeleton based on input from a computer vision module, which detects and analyzes nearby objects. This is performed as several studies suggest that such an approach can be beneficial for controlling assistive robotic manipulators [10].  
Hence, the main contributions of the paper are the following:  
* We design and implement an adaptive semi-autonomous control scheme based on computer vision and evaluate it in the context of controlling an upper limb exoskeleton through a tongue-based interface.
* We evaluate the effectiveness and intuitiveness of various control schemes for performing semi-autonomous tongue-control of an upper limb exoskeleton, through studies including both participants with and without tetraplegia.