NRI: Planning, Collaborative Guidance and Navigation in Uncertain Dynamic Environments

University Of New Mexico, Albuquerque NM

Investigators

Abstract

Navigation in dynamic, uncertain environments is a difficult yet ubiquitous problem in diverse applications such as search and rescue, coordinated movement, distributed monitoring and surveillance. Collaborative solutions are highly promising because of their potential to exploit strengths of both the human and the automation. However, major challenges in collaborative navigation include not only the ability of the underlying automation to effectively handle novel scenarios and changing environments that may not have been considered at the design stage, but also human-automation interaction requirements. The design of methods and tools that can address these challenges could enable fundamentally new functionality in collaborative human-robot systems. The novelty of the proposed research is in the integration of control theory, motion planning, and human guidance to provide highly effective solutions for navigation in highly dynamic and uncertain environments. The proposed project will also create opportunities to involve under-represented minorities in K-12 outreach and in undergraduate and graduate research, to facilitate interdisciplinary collaboration, and to develop a new interdisciplinary graduate course. This proposal aims to develop a generic framework for collaborative navigation in complex environments that can accommodate hundreds of moving obstacles (with possibly stochastic dynamics), non-trivial static obstacles, and humans in the loop. We propose to a) evaluate the tradeoff between short-term and long-term information for both users and autonomous systems in highly dynamic environments, b) extend our existing algorithmic techniques to environments of higher complexity, e.g., multi-robots and non-planar environments, c) design and test several user-interfaces, which satisfy pre-determined conditions for user-observability and user-predictability, for their effectiveness in improving safe navigation, and d) experimentally validate our existing setup for collaborative navigation in dynamic, uncertain environments via an Android app. We will develop tightly coupled planning and control tools, integrate human guidance and decision making with automated tools, and complete a rigorous analysis of safety in highly dynamic environments with uncertainty. The developed methods will be validated in multiple environments, with human subjects, and on a micro robot testbed.