Tell Me Where to Go: A Composable Framework for Context-Aware Embodied Robot Navigation

Humans have the remarkable ability to navigate through unfamiliar environments by solely relying on our prior knowledge and descriptions of the environment. For robots to perform the same type of navigation, they need to be able to associate natural language descriptions with their associated physical environment with a limited amount of prior knowledge. Recently, Large Language Models (LLMs) have been able to reason over billions of parameters and utilize them in multi-modal chat-based natural language responses. However, LLMs lack real-world awareness and their outputs are not always predictable. In this work, we develop NavCon, a low-bandwidth framework that solves this lack of real-world generalization by creating an intermediate layer between an LLM and a robot navigation framework in the form of Python code. Our intermediate shoehorns the vast prior knowledge inherent in an LLM model into a series of input and output API instructions that a mobile robot can understand. We evaluate our method across four different environments and command classes on a mobile robot and highlight our NavCon's ability to interpret contextual commands.Comment: 8 pages (24 with references and appendix), 6 Figure

GUARDIANS final report

Emergencies in industrial warehouses are a major concern for firefghters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist fire fighters in searching a large warehouse. In this report we discuss the technology developed for a swarm of robots searching and assisting fire fighters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also one of the means to locate the robots and humans. Thus the robot swarm is able to locate itself and provide guidance information to the humans. Together with the re ghters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

Advancing automation and robotics technology for the Space Station Freedom and for the US economy

The progress made by levels 1, 2, and 3 of the Office of Space Station in developing and applying advanced automation and robotics technology is described. Emphasis is placed upon the Space Station Freedom Program responses to specific recommendations made in the Advanced Technology Advisory Committee (ATAC) progress report 10, the flight telerobotic servicer, and the Advanced Development Program. Assessments are presented for these and other areas as they apply to the advancement of automation and robotics technology for the Space Station Freedom