1. ROBOTICS AND LUNAR EXPLORATION Ayanna M. Howard, Ph.D. Human-Automation Systems Lab School of Electrical and Computer Engineering Georgia Institute of Technology Acknowledgements: Dr. Edward Tunstel, Lead Engineer, MER Mobility Team Dr. Paul Schenker, Manager, Robotics Space Exploration Technology Program

2. Why Robots? WHY NOT JUST HUMANS FOR PRE-CURSOR LUNAR MISSIONS?? Has been PROVEN that Human Control is NOT Safe!! When steering commands are delayed by communications there is a tendency for the operator to over-steer and lose control. It was shown that with a communication delay corresponding to round trip to the Moon (about 2 1/2 seconds) the vehicle could not be reliably controlled if traveling faster than about 0.2 mph (0.3 kph) [Adams 1961]

3. Why Robots? WHY ROBOTS FOR SORTIE MISSIONS?? A complex extended mission will require more tasks than humans can support without help. Crewmember time will be a very valuable resource, so mundane tasks should be minimized. This will allow the crew to apply their expertise where it is most needed. Extra-vehicular activity is particularly risky for humans, but will be unavoidable for a complex mission. –Spacesuits restrict mobility, dexterity, and visual field –Suit pressurization opposes bending motions, reducing effective stamina –Limited time during EVA, plus time for pre-breathing

4. More increasingly, robotic vehicle autonomy is necessary for ensuring science return and achieving overall success of planetary surface missions Recent and planned missions include requirements that rely on autonomous mobility and manipulation technologies to achieve mission success –Mars Pathfinder (MPF) (Sojourner rover): traverse to science targets to acquire spectroscopic measurements –Mars Exploration Rover (MER): traverse to new locations over terrain of some reference complexity and accurately place instruments onto science targets maintain estimated position knowledge within some % of distance traversed –Mars Science Laboratory (MSL); ExoMars Rover Functionality

5. MER Benchmark for Rover Autonomy MER represents the longest deployment of planetary rovers in remote planetary surface environments. A new benchmark in planetary robot autonomy and human-robot systems (in addition to a landmark in planetary in situ scientific exploration) Assess rovers’ performance (surface navigation and instrument placement) to facilitate understanding of future robotic systems by providing metrics derived from Mars performance data for Spirit and Opportunity.

6. Surface Operations Rover technologies can be classified based on four common technologies

7. Surface Mobility Characteristics include: –Distance/range –Speed –Terrain accessibility (slopes, obstacles, texture, soil) –Load carrying capability –Agility (turn radius) –Access (vertical, sub-surface, small spaces, etc.) Movement is a key requirement for autonomous planetary rovers. Focus is to enable planetary rovers to traverse long distances on challenging terrains safely and autonomously. Trade-offs on design include: –Maneuverability –Traction –Climbing ability –Stability –Efficiency –Environmental impact HumAnS Lab, GeorgiaTech

8. Science Perception, Planning, Execution Provide ground tools for scientists to plan days events, while allowing generation and robust execution of plans with contingencies, concurrent activities, and flexible times Characteristics Include: Sensing Analysis (e.g. chemical analysis) Data processing Understanding of Context, Knowledge, and Experience

9. Human-Robot EVA Interactions Characteristics –Ground based supervised autonomy (versus tele-operation) Operator may enter planning, monitoring, and control at multiple levels –Proximate telepresence –Shoulder-to-shoulder interaction –Robot assistants HumAnS Lab, GeorgiaTech

10. Instrument Placement/Sample Manipulation Common Characteristics Include: –Mass and volume –Fragility, contamination, reactivity –Manipulation technique: Torque, Precision, Complexity of motion –Repetitive vs. unique –Time –Moving with minimal disturbance Arm placement and object manipulation involves touching a specific point in 3D space, grasping an arbitrarily oriented object in 3D space, and moving an object from one location to another. The CHALLENGE Get there efficiently and safely And, move the arm so that it does not try to violate its own joint limits And ensure that it does not hit itself or the rest of the robot, or any other obstacles in the environment

11. Capability Benchmarks: MER to MSL

12. Current State-of-the-Art Autonomous mobility and sample access –MER mobility: 10-120 m/sol to commanded point with > 90% success, < 20 degree slopes, sparse obstacle field –MER visual odometry: ~2% accuracy over distance traveled –MER sample access: RAT, wheel scuffing of soil –Deep Space 2: Small, sub-surface micro probe, ~50cm access Autonomous instrument deployment –MPL arm: ~2 m reach, 4 DOF, operated from fixed platform –MER arm: 90 cm reach, 4 DOF, operated from mobile base On-board autonomous science –Human-commanded on per-sol basis –Fixed sequences Human-robotic field science –No operational experience Human-robot interaction –Sojourner/MER: Ground teleoperation –MER: Commanded on per-sol basis =>Laboratory, and some field, demonstrations of long-range navigation (< km per command cycle), 7DOF arms, meter-deep drilling, single instrument placement, autonomous science planning and execution, robotic assistants, etc.

13. goal autonomous traverse route partial panorama goal Challenges to Mobile Autonomy APPROACH & INSTRUMENT PLACEMENT: Autonomous placement of a science instrument on a designated target, specified in imagery taken from a stand-off distance. Precise contact measurements and autonomous sample manipulation. Drilling to 1000m depth. Visual servoing/approach to multiple targets in single command cycle. AUTONOMOUS TRAVERSE: Autonomous traverse, obstacle avoidance, and position estimation relative to the starting position. Single vehicle to access all terrain types, cover long distances, and carry/deploy a payload. ONBOARD SCIENCE: Autonomous processing of science data onboard the rover system, for intelligent data compression, prioritization, anomaly recognition. Human level cognition and perception of science opportunities. cameras & spectrometer drilling & scooping processing and caching SAMPLING: Sampling, sample processing, and sample caching through development of controls for new system components.

14. Challenges: Lunar Characteristics Gravitational Characteristics Low gravity: 1/6 Earth’s - low energy locomotion Rotational/Orbital Characteristics Communications easy from near side, difficult from far side, periodic at poles Long days, long nights: 14.6 days light, 14.6 days dark Sun skims horizon at poles Permanent shadows in polar craters Earth-to-Moon Characteristics 2.5 second round-trip speed-of-light delay

15. Challenges: Lunar Characteristics Impact Craters Microcraters: 10 -8 - 10 -3 meters Regolith craters: 10 -2 - 10 3 meters Large craters/Impact basins - 10 2 - 10 6 meters Volcanic Channels, Collapsed Lava Tubes, Mountains Regolith 2-8 meters deep in maria regions 15 meters deep in lunar highlands Dust Extremely fine, electrostatically charged

16. Capability Trends

17. Time Estimates for Space Robotics

18. EXAMPLE: Rover Metrics LEMUR, JPL

19. Sortie Missions: Robotics Proximate Telepresence In many missions, the humans will be near the robots but will be supervising them from a safe distance (e.g., in a habitat or on orbit). To facilitate the interaction, the robots should have capabilities similar to humans (especially in terms of manipulation) and the level of control between robots and humans should be highly flexible (“sliding autonomy”). Situational awareness of the supervisor needs to be high, which can be facilitated with both multi-modal feedback and high-level interpretation (by the robot) of sensor data. Safeguarding to prevent harm to the robots is critical. Shoulder-to-Shoulder Interaction In some missions, humans and robots will be co-located on site, working together. At a basic level, the robots will need to understand and communicate with the astronauts using both speech and gesture. In addition, in many cases they will need to infer (without communication) the behaviors and intentions of the astronauts and alter their activities accordingly to support the astronauts’ goals. Safeguarding to prevent harm to the humans is critical. (Some risk)

20. NASA-JSC Boudreaux –an Extra-Vehicular Activity (EVA) Robotic Assistant Specific sub-capabilities include: –Site development (survey, excavation, resource deployments) –Site maintenance (inspection, repair, assembly, materials transport) –In situ resource production (robotic support to extraction, transport, manufacturing) –Field logistics and operations support (materials & equipment transport & warehousing) –Human-robot interaction (H/R task allocation, teleoperation, remote supervisory control, etc.) Surface EVA Assistance JSC

21. Why EVA robots must assist humans Humans are necessary for surface EVAs –Adaptability, Intelligence, Dexterity Robots are necessary for surface EVAs –Pack mule, extra hand, situational awareness –Put robots at risk instead of humans JSC

22. Robot Capabilities Have a robot assist an astronaut in deploying science instruments (e.g. geophones) Various forms of interaction: voice commanding, gesture recognition, dialogue, full autonomous mode, traded autonomy Various forms of Capabilities: mobility, manipulation, autonomous traversal of rugged terrain, tracking of suited crew member Robonaut, JSC

23. Benefits for Sortie Missions Robotic ISRU, robotic precursor preparation and ongoing robotic mission support are enabling for due to impact on sustainability and affordability. Human safety is enhanced through precursor robotic site preparation. Field operations productivity is enhanced through robotic “mule” support and robotic mobile communication networking. Astronaut productivity is enhanced by lowering maintenance and inspection overhead assigned to human crew. Ground-crew interaction productivity is enhanced by improved human-robot interfaces.

24. Summary State-of-the-Art Robotics has not been used for lunar exploration. State-of-art can be indirectly measured from sub-capabilities with terrestrial deployment, TRL6 and below: –Site development: Autonomous robotic excavation and site shaping has been demonstrate by joint CMU – Caterpillar front loader system. –Site development: Communication infrastructure deployment by various university research groups in the DARPA Centibots program has set up networks using robot teams in unexplored urban areas. –Site maintenance: Dexterous manipulation under teleoperation has been demonstrated in analog environments by both Ranger and Robonaut research teams with astronaut glove-level dexterity and 6x slowdown. –Field logistics and operations support: Long-distance autonomous navigation has been demonstrated on the order of 100km total distance traveled. –Field logistics and operations support: Architectures for perception, planning and control have demonstrated efficacy in Mars-analog tests at JPL and Ames.

25. Deliverables for Capability

26. Metrics for Sortie Missions

27. Conclusions NASA manned and unmanned missions will be carrying out increasingly challenging tasks on the lunar surface: Habitat construction and long term habitation Mining and in-situ resource utilization Deep drilling Scientific laboratory tests currently done only on earth Biological and habitability analysis Robotics is key for providing both enabling and enhancing capabilities necessary for achieving the goals of these future missions.