Effects of automation and task load on task switching during human supervision of multiple semi-autonomous robots in a dynamic environment

The present study assessed the impact of task load and level of automation (LOA) on task switching in participants supervising a team of four or eight semi-autonomous robots in a simulated ‘capture the flag’ game. Participants were faster to perform the same task than when they chose to switch between different task actions. They also took longer to switch between different tasks when supervising the robots at a high compared to a low LOA. Task load, as manipulated by the number of robots to be supervised, did not influence switch costs. The results suggest that the design of future unmanned vehicle (UV) systems should take into account not simply how many UVs an operator can supervise, but also the impact of LOA and task operations on task switching during supervision of multiple UVs.

The findings of this study are relevant for the ergonomics practice of UV systems. This research extends the cognitive theory of task switching to inform the design of UV systems and results show that switching between UVs is an important factor to consider.     

Investigating the effects of experience on human performance in an object-tracking task: a case study of manual rendezvous and docking

Human involvement with the manual control of object-tracking tasks, such as manual rendezvous and docking, can enhance the flexibility of the task. The operator is required to make decisions as precisely as possible when a chase vehicle is approaching the target vehicle. As the level of mental workload is intensively increased, the operator's perception and decision-making with tracking error-correcting purposes should be properly identified in multiple degrees of freedom (DOFs). The two experimental studies in this paper were conducted for object-based selective attention in six DOFs and object-pointing manipulation under the zero resistance circumstance, which were correlated with human performance when a chaser approached a target spacecraft; the effects of experience level on the two important factors are presented herein. The experimental results demonstrated that some performance details between the novice and experienced groups were different in terms of the attentional priority of multiple DOFs and lateral/vertical movement for deviation error correction, which could provide a certain reference for a cognitive–behavioural model and assist the operator in obtaining proper or even optimal decision-making or operating instructions to improve their adaptation to selective attention and object-pointing manipulation, for preventing accidental manipulation and performance degradation.     

Path-based approach to integrated planning and control for robotic systems: A path-based approach provides an analytical integration of robot planning and control. As a result, the task level control can be achieved, and the system is capable of coping with unexpected or uncertain events

Our newly developed event-based planning and control theory is applied to robotic systems. It Introduces a suitable action or motion reference variable other than time, but directly related to the desired and measurable systems output, called event. Here the event is the length of the path tracked by a robot. It enables the construction of an integrated planning and control system where planning becomes a real-time closed-loop process. The path-based integration planning and control scheme is exemplified by a single-arm tracking problem. Time and energy optimal motion plans combined with nonlinear feedback control are derived in closed form. To the best of our knowledge, this closed-form solution was not obtained before. The equivalence of path-based and time-based representations of nonlinear feedback control is shown, and an overall system stability criterion has also been obtained. The application of event-based integrated planning and control provides the robotic systems the capability to cope with unexpected and uncertain events in real time, without the need for replanning. The theoretical results are illustrated and verified by experiments.