This study investigated the impact of the design of robotic navigation algorithms on human performance in a searching task. Participants searched for targets in a real-world environment using a tele-robot in the context of an urban search-and-rescue task. Participants were assigned to one of three conditions for the navigation of the tele-robot around the search area: tele-operation or automated navigation using one of two different algorithms.

Participants in the left-wall algorithm condition found significantly more targets that were of medium-high difficulty to identify. In addition, participants in the tele-operation condition used two distinctly different approaches to navigate around the search area. This evidence suggests that the development of path planning algorithms needs to be tailored to the operator. The knowledge that there are differences in algorithms from the human perspective provides an additional metric for the robotics community to decide between algorithms that are otherwise equivalent. Acknowledging the effect of differences in these algorithms when making design choices is important for the success of the human-robot partnership.