Traclabs Inc. — National Aeronautics and Space Administration SBIR Phase I: Z5
Traclabs Inc. — SBIR Phase I award from National Aeronautics and Space Administration.
- Amount
- $124,994
- Agency
- National Aeronautics and Space Administration
- Program / Phase
- SBIR · Phase I
- Topic
- Z5
- Solicitation
- SBIR_20_P1
- NAICS
- —
- Place of performance
- TX
- Period
- 2020-07-30 → 2021-03-01
Description
One major hurdle to robust multi-robot operations in space is the same hurdle faced by multi-robot applications on Earthmdash;co-located, yet independent, robotic quot;individualsquot; do not adequately share state information. State information can include: environmental knowledge, current position and velocity, future state estimates, what task is currently being performed, what resources are needed to complete the current task, where shared resources may be located, and even data about if/why execution failed. Sharing some amount of state information is not only a necessity for multi-robot tasks that require cooperation, but is critical even for groups of independent robots that must share resources.TRACLabs proposes to create a collection of software processes, called PLUMMRS, that will facilitate sharing of environmental and internal state information to enable safe, efficient navigation and manipulation tasks by heterogeneous robot teams working in a shared workspace. The goal of PLUMMRS (Plan Ledgers and Unified Maps for Multi-Robot Safety) is to provide simple APIs for existing single-agent planning and execution systems to leveragemdash;allowing them to be safely used in multi-agent contexts. PLUMMRS can be used by any individual robot in a group of robots to contribute to, and benefit from, a unified model of not only geometric and semantic perception data but also of expected and currently executing motion- and task-level plan data. PLUMMRS is not a planning framework, as each robot is expected to have its own quot;black-boxquot; motion- and task-planning capabilities; however, PLUMMRS can be used by both motion- and task-planning amp; control systems as 1) an oracle of shared knowledge, 2) a safety monitoring watchdog based on shared knowledge, and 3) an arbiter (scheduler) that attempts to loosely coordinate the short-term and long-term desires proposed by all robots that are trying to independently complete their tasks while sharing a workspace and physical resources.