RI: Small: Robotic Path Planning to Reveal Wireless Rays - A New Foundation for the Optimization of Networked Robotic Operations

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

A robotic network can have a tremendous impact in many different areas such as emergency response, national security, and mobile service provisioning. In such systems, a team of unmanned vehicles are tasked with information gathering and cooperation to accomplish a given mission. Wireless communication is an integral part of such a system as an unmanned vehicle needs to connect to other nodes or to remote operators in order to transfer sensing data and/or receive control commands. Since a robot’s path directly affects its link quality, an unmanned vehicle needs to take the communication quality into account during path planning. This then requires an unmanned vehicle to have an accurate prediction of its link quality at unvisited locations. Accurately predicting the channel quality, however, is a considerably challenging problem and an open one, due to the high spatial variations of the channel power. This project enables the robust cooperation of a team of unmanned vehicles by developing new predictive wireless channel models and its corresponding co-optimization with sensing and path planning, which can significantly impact the area of robotics. The project also has an educational component, leveraging appeals of both robotics and communications, to reach out to the young minds. This project develops a new multi-disciplinary paradigm for the robust networked operation of unmanned vehicles. The first research task shows it possible for the robot to reveal the makeup of the incoming wireless rays, based only on its onboard received channel power measurements. More specifically, it proposes a novel combination of path planning and information processing that can reveal the makeup of the rays, enabling the robot to learn considerably more about the channel than the measured received power. This new approach has a significant implication for robotic field operation as the project addresses. More specifically, the second major task builds on the first one in order to develop a new framework for robotic channel prediction. The third major task then develops a multi-disciplinary design that properly co-optimizes the new predictive channel models with sensing and path planning decisions, in order to enable the robust networked operation of unmanned vehicles. Finally, the overall new design paradigm is tested on a robotic testbed. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.