To Örebro University

Caregivers in eldercare can benefit from telepresence robots that allow them to perform a variety of tasks remotely. In order for such robots to be operated effectively and efficiently by non-technical users, it is important to examine if and how the robotic system's level of automation (LOA) impacts their performance.  The objective of this work was to develop suitable LOA modes for a mobile robotic telepresence (MRP) system for eldercare and assess their influence on users' performance, workload, awareness of the environment and usability at two different levels of task complexity. For this purpose, two LOA modes were implemented on the MRP platform: assisted teleoperation (low LOA mode) and autonomous navigation (high LOA mode). The system was evaluated in a user study with 20 participants, who, in the role of the caregiver, navigated the robot through a home-like environment to perform control and perception tasks. Results revealed that performance improved in the high LOA when task complexity was low. However, when task complexity increased, lower LOA improved performance. This opposite trend was also observed in the results for workload and situation awareness. We discuss the results in terms of the LOAs' impact on users' attitude towards automation and implications on usability.

Mobile robotic telepresence (MRP) systems feature a video conferencing interface on a mobile robot, enabling pilot users to remotely control the robot while communicating with a local user. For older adults in an assisted living facility, the operators are mostly caregivers or remote family members. This small-sample usability testing aimed to evaluate the use of MRP by the older adult. Participants navigated the robot to locations in the home, e.g., to check if the front-door is closed. Two levels of automation were introduced; assisted teleoperation and autonomous. Observations revealed that the older adults enjoyed the dexterity with which the robot could be teleoperated in the assisted teleoperation mode. Yet, they preferred the operation of the MRP at the autonomous mode where the robot navigated autonomously towards the locations the user indicated. Usability, preference and objective findings raise awareness regarding elder care assistive robot developmental factors. Future experimental plans are discussed.

Telepresence robots, similar to other teleoperated robots, can benefit strongly from shared autonomyas a way to enhance ease of use for the operator. With ever-increasing capabilities of autonomousrobots, it is crucial to understand what can be automated and under which circumstances. We argue that within a dynamic environment, the allocation of tasks between human and robot should not be fixed, but rather adaptable, taking into account the current state of the environment.

Various human-robot collaboration scenarios mayimpose different requirements on the robot’s autonomy, ranging from fully autonomous to fully manual operation. The paradigm of sliding autonomy has been introduced to allow adapting robots’ autonomy in real time, thus improving flexibility of a human-robot team. In sliding autonomy, functions can be handed over between the human and the robot to address environment changes and optimize performance and workload. This paper examines the process of handing over functions between humans by looking at a particular experiment scenario in which the same function has to be handed over multiple times during the experiment session. We hypothesize that the process of function handover is similar to already well-studied human-robot handovers which deal with physical objects. In the experiment, we attempt to discover natural similarities and differences between these two types of handovers and suggest further directions of work that are necessary to give the robot the ability to perform the function handover autonomously, without explicit instruction from the human counterpart.

Sliding autonomy is used in teleoperation to adjusting a robot's level of local autonomy to match the user's needs. We claim that sliding autonomy can also improve mobile robotic telepresence, but we argue that existing approaches cannot be adopted to this domain without adequate modifications. We address in particular the question of how the need for autonomy, and its appropriate degree, can be inferred from measurable information.