AI in Space – Lessons From NASA’s Deep Space 1 Mission Ron Keesing Dept. Of Maths & Computing Science University of the South Pacific

Overview NASA’s Deep Space 1 Mission A brief introduction to AI Why use AI in space? The Remote Agent Future Directions

NASA’s Deep Space 1

NASA’s Deep Space 1 Technology First mission of NASA’s New Millenium Program. Primary mission goal was to demonstrate new technologies.

NASA’s Deep Space 1 Innovation First demonstration of Ion Propulsion System Engine AI system for spacecraft command and control (Remote Agent) 10 other technologies

NASA’s Deep Space 1 Ion Propulsion System Engine

NASA’s Deep Space 1 Exploration Launched in October, 1998 Successful flybys of Asteroid Braille (26 Kms) Closest asteroid approach to date Comet Borrelly Best data ever collected from comet

NASA’s Deep Space 1 Exploration – Launch

NASA’s Deep Space 1 Exploration – Artist’s conception

NASA’s Deep Space 1 Exploration - Encounter with Comet Borrelly

A Brief Introduction to AI What is artificial intelligence? Creating machines that behave “intelligently”. How would you know an “intelligent” machine if you saw one? The Turing Test

A Brief Introduction to AI Early predictions (1950s) were very optimistic. Computers would soon: Win World Chess Championship. Understand spoken language. Be as “smart” as people.

A Brief Introduction to AI HAL-9000 from “2001 – A Space Odyssey”

A Brief Introduction to AI HAL-9000 from “2001 – A Space Odyssey”

A Brief Introduction to AI HAL-9000 from “2001 – A Space Odyssey”

A Brief Introduction to AI Creating “intelligent” computers has proven far more difficult than imagined. 50 years to beat world chess champion. Not close to understanding language. No one even thinks about a computer passing the Turing Test anymore…

A Brief Introduction to AI Human beings are much smarter than we gave ourselves credit for. Solving differential equations is easy. Catching a ball is hard. Storing lots of information is easy. Understanding it is hard.

A Brief Introduction to AI Even though AI is hard, we’ve developed a lot of ways to make machines “smarter”. Planning Automated Reasoning Agents

A Brief Introduction to AI Planning Decomposing high-level goals into individual tasks that can achieve these goals efficiently Robots that can manipulate objects. Systems for optimizing manufacturing processes.

A Brief Introduction to AI Automated Reasoning Making inferences from limited information based on knowledge of the domain. Medical diagnosis Theorem proving

A Brief Introduction to AI Agents Systems that can perform complex tasks autonomously. Web search agents that can navigate the web looking for specific pieces of information.

Why Use AI In Space? Conventional model of spacecraft control Ground control sends a plan. Spacecraft executes that plan. If anything goes wrong, spacecraft enters “safe mode” and calls ground control.

Why Use AI In Space? Problems with “ground control” approach: Expensive May miss opportunities. Sometimes it’s more dangerous to wait for help. Some missions can’t be run from ground.

The Remote Agent An autonomous system for spacecraft command and control 3 components Planner Inference system (MIR) “Smart Executive”

The Remote Agent Planner Takes mission goals from ground control and creates a plan to satisfy them Plans for limited resources (power). Plans satisfy numerous constraints (orientation, communication, state of devices).

The Remote Agent Planner OpNav IPS Thrust ACS Turns MICAS Power MICAS Imaging Nav OD Planning

The Remote Agent Inference system (MIR) Gets information from sensors. Deduces state of spacecraft using model-based reasoning. Suggests ways to reconfigure if devices fail.

The Remote Agent Inference system (MIR)

The Remote Agent “Smart Executive” Sends commands to spacecraft to execute the plan. Executes the plan flexibly, including trying multiple methods if necessary. Recognizes when a plan has failed and triggers replanning.

The Remote Agent “Smart Executive” (to_achieve (IPS_THRUSTING ips level) ((ips_is_in_standby_state_p ips) (sequence (achieve (power_on? 'ega—a)) (command_with_confirmation (send—ips—set—thrust—level level)) (send—acs—change—control—mode :acs—tvc—mode)))) ((ips_in_thrusting_state_p ips) (send—ips—change—thrust—level level))) (t (fail :ips_achieve_thrusting)))

The Remote Agent Experiment The Remote Agent took control of DS-1 for 3 days. Validated all objectives Demonstrated ability to formulate plans to satisfy mission goals. Demonstrated ability to diagnose faults and reconfigure to perform tasks. Demonstrated plan failure, recovery, and replanning.

The Remote Agent Experiment Lessons from using AI on DS-1. An autonomous system can successfully control a complex spacecraft. Opens the door to new types of missions and a new relationship between ground and spacecraft. The RA architecture is a powerful approach to building robust autonomous systems

Future Directions For AI In Space Autonomous rovers Manned mission to Mars Formation flying Many-agent approaches