A human-robot collaborative Traveling Salesman Problem: Robotic site inspection with human assistance

摘要

In this paper, we consider a collaborative human-robot Traveling Salesman Problem (TSP), where a robot is tasked with site inspection and target classification, under a limited motion energy budget and with a limited access to a human operator. More specifically, a robotic field operation is considered where a robot has to co-optimize seeking human assistance (via asking questions) and selective TSP tour design (for a closer inspection) based on an initial remote sensing. The robot has a limited budget for both communication with the human operator and site inspection motion consumption. By utilizing our past work on the target classification performance of humans and robots, we show how the collaborative human-robot TSP can be solved under limited resources. We further theoretically characterize the average correct classification probability as a function of the given number of questions to the human operator and the given motion energy budget. Extensive simulation results confirm our theoretical derivations.