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ROBOTICS at Carleton the core in-situ resource utilisation (ISRU) technology Prof Alex Ellery Space Exploration Engineering Group (SEEG) Dept Mechanical & Aerospace Engineering Carleton University RESOLVE PAYLOAD In-situ resource


  1. ROBOTICS at Carleton – the core in-situ resource utilisation (ISRU) technology Prof Alex Ellery Space Exploration Engineering Group (SEEG) Dept Mechanical & Aerospace Engineering Carleton University

  2. RESOLVE PAYLOAD In-situ resource utilisation (ISRU) – exploitation of extraterrestrial resources - is the key to  development of the space environment  RESOLVE is a US-led mission to lunar south pole Aitken basin  RESOLVE payload (US) to demonstrate in-situ resource utilisation for the first time  Multiple scientific instrument package of 72 kg  Water ice extraction  Oxygen generation through hydrogen reduction of ilmenite Canadian rover and drill – industrial team   Canadian science definition team (i) Soil property extraction during traverse and drilling (ii) Visual feature extraction to recognise signs of ice and/or ilmenite  Full teleoperation is infeasible  Autonomous Robotics is core technology for ISRU

  3. A NEGLECTED RESOURCE IN CANADA Universities are neglected resources – this is particularly the case in space engineering   Kapvik was a 30 kg fully-functional micro-rover prototype for CSA administered by MPB with Carleton University as technical lead – it was built with a clear PATH TO FLIGHT  Carleton University’s Space Exploration Engineering Group performed the initial design and specifications of the entire rover and its performance parameters, and performed detail design (from scratch), manufacture, assembly and test of Kapvik chassis, body structure, camera/uv pan-tilt system, avionics control architecture, avionics packaging and harness routing, and major aspects and interfaces of vision and autonomous navigation system for only $320k over 2.5 years – at all times, we were on budget and on time  It is still working 2 years (the only fully-functional micro-rover platform at CSA) after delivery undergoing deeper and longer tests beyond its original design specifications  In Europe and US, university teams are valued and trusted to develop and build spaceflight hardware – scientific instruments (eg. QMC), full spacecraft subsystems (eg. APL), and innovative technology demonstrators (cubesats – everyone and his dog)  Micro-rovers, manipulators and other micro-systems (eg. micro-penetrators) are within the capabilities of universities - universities are in principle no less capable with no greater risk of delivering quality products than companies We are cheap in financial cost but rich in capability – if you want extreme value for money,  come to us!

  4. KAPVIK MICRO-ROVER  Fundamentally new concept - exchangeable modular chassis - rocker-bogie (built) and ELMS (detailed design only)  Exchangeability within three minutes by a single human using a single tool

  5. SOIL PARAMETER ESTIMATION  Soil parameters are required to perform automated traction control                  [( / )( ) ( 1 )(s si ) r K a s ( tan ) 1 c e a  To extract soil parameters online, we implemented Instrumented rocker-bogie chassis for Kapvik microrover

  6. PETRIE ISLAND FIELD TESTS

  7. WATER ICE DETECTION BY ROVER  MLP neural net models based on Bekker-Wong traction theory  Online extraction of cohesion 3.7 kPa and friction angle of 28 degrees (sandy- loam)  Online detection of surface water ice and evaporated fluffy regolith (RESOLVE)  Input to traction controller to minimise slip (and power)

  8. ELBOW-MOUNTED PAN-TILT UNIT

  9. STEREOVISION SYSTEM Vision processing filters extract objects Disparity map extracts 3D point cloud for input to SLAM

  10. AUTOMATED ROCK DETECTION ON MARS

  11. LIDAR PROCESSING  To efficiently parse large point clouds from laser rangefinder as well as classify different terrain for path planning, neural network classification algorithm was used .

  12. SELF-LOCALISATION & MAPPING (SLAM) SLAM is necessary to self-locate in the environment – it is first stage of AutoNav  Object surfaces and terrain estimated using meshing algorithms  Delauney triangulation to self-localise  SLAM using unscented (cubature) Kalman filter (UKF)  SLAM-based autonomous navigation simulation  Path-planning is second phase of AutoNav  Path-planning development with NEPTEC using  ClearPath Husky rover

  13. SLAM USING D* PLANNER

  14. POTENTIAL FIELD-BASED PATH PLANNER USING WAYPOINTS

  15. POTENTIAL FIELD NAVIGATION ON MARS Rock distributions for VL1, VL2, MPF & MER-A

  16. MARS ANALOGUE OPERATIONS Understanding rover operational constraints Jeffreys Asbestos mine Quebec with large science team Pioneer robot used for 3 day field deployment Mars methane plume source tracking algorithm

  17. AUTONOMOUS VISUAL SCIENCE  There are several approaches to visual feature discovery  In order to explore the information content in texture, we are ignoring colour for the moment – in addition, regolith covering makes colour differentiation unreliable  Shale Schist Igneous  Resolution is critical for extracting useful features – we have thus far worked at 1m stand-off distances

  18. HARALICK-BASED TEXTURE ANALYSIS  The use of Haralick parameters offers one potential approach that is computationally efficient – we are currently investigating this technique applied to rocks (applicable to soil texture)  Basic image statistics Entropy measures (one of several Haralick  parameters  Investigation of image pre-processing (GCOM) matrix

  19. GABOR FILTER-BASED TEXTURE ANAYSIS Canny edge detector Gabor filter Gabor filter offers greater textural richness – they are direction-sensitive   Human visual processing implements GF  Gabor filter bank of 80 filters for pattern recognition of textures  High computational complexity  (a) add colour/NIR channels  (b) apply to geological terrain features

  20. BAYESIAN NET CLASSIFIER Rock classification implements “robotic geology” 

  21. AUTOMATED CAMERA CONTROL  Active vision introduces serendipitous science search mode during rover traverse  Rapid-slew pan-tilt unit implements foveated vision to minimise image processing  Salience introduces randomised but targetted search  Kalman filter-trained neural net forward model compensates for lack of camera IMU  This emulates function of human cerebellum  7 DOF Barratt arm control system will validate Applicable to on-orbit servicing – start of  space-based manufacturing

  22. ON-ORBIT SERVICING

  23. NOVEL DRILLING TECHNOLOGIES We have been examining bio-inspired techniques to drilling Eliminates need for automated drill string assembly required in deep rotary drilling, eg. ExoMars Wood wasp ovipositor

  24. MICRO-PENETRATORS  Micro-penetrators may be deployed to the Moon and/or asteroids to investigate surface and subsurface properties – initial survey missions

  25. LUNAR PENETRATOR TRAJECTORY

  26. ASTEROID IMPACT & DEFLECTION ASSESSMENT We are proposing a 3 kg micropenetrator with a minimal suite of micro- instruments for ESA’s AIM spacecraft to measure debris impacts generated by US DART Accelerometer is GP instrument Seismometer is central for internal geophysics to determine internal consistency Temperature measurements for thermal inertia measurements This provides basic measurements of asteroid surface and Subsurface as precursor to ISRU and/or impact mitigation

  27. VIFFING MICRO-PENETRATOR FOR ENCELADUS

  28. CONCLUSIONS  Canada has an opportunity to participate in the first ISRU mission - RESOLVE  Once demonstrated, ISRU will become more attractive and accepted  ISRU represents the “next big thing” in space commerce  Key concept – robotic factory represents a “mass amplifier” that dwarfs the limits of launch: it amplifies by producing ~10^5 times its own mass in product  We are interested in the application of 3D printing to ISRU  Key is to match material manufacture to printing technology  One possible space market is the manufacture of simple space modules to construct a space sunshield (independence from human space programme)  Our business to make robotic ISRU possible  We are always in search of R & D funds!

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