Minimizing Robot Navigation Graph for Position-Based Predictability by Humans

Sriram Gopalakrishnan (Arizona State University), Subbarao Kambhampati (Arizona State University)

Abstract

When multiple humans and robots are moving in spaces like restaurants, hospitals, or banks, making the robot's movements easy to predict can help the humans co-navigate the space with the robots. Since people would be busy with their own goals, they are not paying close attention to the prior movements, or goals of multiple robots. So predictability from the robot's current position alone would help. With this in mind, we propose using an algorithm to lay out fixed paths for the different tasks the robots would do, such that predictability from only the current position alone is optimized, and motion costs are kept within acceptable bounds.