Autonomy and Operation Interactive session ADCSS 2018 ESTEC 17/10/2018

Transcription

1 Autnmy and Operatin Interactive sessin ADCSS 2018 ESTEC 17/10/2018

2 ADCSS 2018 Interactive sessin The sessin is meant t prvide pen and interactive discussin abut several tpics f interest, spanning ptentially several disciplines. The sessin will be run as described belw: Fur Tpics have been selected and they will be briefly intrduced by selected mderatrs: 1.Digital engineering/transfrmatin 2.Autnmy and peratin 3.COTS avinics 4.Security. T stimulate interactin, dedicated panels will be set-up fr each tpic. Arund these panels attendees are encuraged t actively discuss the subjects with the help f the mderatr, addressing in particular the Strength, Weaknesses, Opprtunities and Threats (SWOT) f each tpic. Attendees are encuraged t walk between the tpics and participate in several discussins. At the end f the sessin the mderatrs will draw the cnclusins fr each Main Tpic that will be eventually presented t the audience. 2

3 Autnmy Definitin : Space Missins needs Autnmy is the capacity f a system t make a decisin abut its actins, withut the invlvement f anther system r peratr. Within the framewrk f Space missins with an increasing level f cmplexity, a higher level f integrated decisin making is key. Autnmy will bring: Imprvement f Reactivity, agility and versatility wrt missin requests and/r envirnment OPEX cst reductin and less Grund/Human interventin Deal with telemetry link ptimizatin, large cmmunicatins delays, jammed cmmunicatins, military zne Access t challenging areas fr Humans and/r fr manned assets Imprvement f missin Reliability, Availability, Maintainability What categries f missins will benefit frm autnmy? Space Explratin: Explratin & discvery f ur Slar System, samples return & landing, rvers/ ascent & descent vehicles Missins within the Earth vicinity (altitude GEO): Earth bservatins, Electric Prpulsin (EP)- / Chemical Prpulsin (CP)- based rbit cntrl, EP-based transfer t GEO Prximity Operatins: Frmatin flying, In-rbit servicing & capture f space assets, assembly f large structures 3

4 Autnmy Definitin : Functins and Technical areas Autnmus GNC : Earth Orbit Cntrl Guidance fr LEO agile satellite Earth Orbit Raising fr MEO/GEO Debris & cllisin avidance End f life de-rbitatin Interplanetary navigatin Prximity peratins Orbital Rendez-vus and Landing Autnmus Cmmand/cntrl & FDIR Grund/ On-Bard sharing CONOPS and Mde transitins Smart and ptimized TM Mass memry and dwnlad planning peratins Intelligent FDIR Operatinal maintenance capability Fleet / cnstellatin management Autnmus Space Rbtics Rbtics arm & samples Rbtics dcking and capture systems In rbit services (refueling, repairing) In Space Manufacturing & Assembly Autnmus Missin Planning Grund Autmatin On-bard tasking autnmy Dynamic prgramming and reactivity Pririties management Alternatives planning Optimised planning Autnmus Paylad Data Prcessing On-Bard Image, SDR, Radar Data prcessing & cmputing Event r change detectin : clud Smart paylads Smart Sensrs (Cameras, Lidar, GNSS) Grund services 4

5 Autnmy Definitin : Enabling technlgies Autnmus GNC : Visn & RF Based Navigatin On-bard guidance Hazard detectin avidance On-bard rbit prpagatin & determinatin Autnmus EOR Re-entry techniques Autnmus Cmmand/cntrl & FDIR Synthetic TCs Mdel-based FDIR File-based peratins Large & intelligent mass memries Inter Satellite Links (ISL) & EDRS Optical & RF ISL Active / smart antennas Autnmus Space Rbtics Autnmus path planning Rbtics arm & jints cntrl Dcking & berthing mechanisms Rbtic Tls interperability & interfaces In Space ALM & assembly End-t-end cntrl Autnmus Missin Planning Multi-agent algrithms Flexible missin plans Real-time tasking Direct tasking Satellite t satellite tasking Autnmus Paylad Data Prcessing High perfrmance cmputing AI & Machine learning Cmplex algrithms Verificatin and Validatin (Behaviral Mdels, frmal techniques ) 5

6 Autnmy Definitin : sme key challenges Which trend : Grund autmatin r On-Bard autnmy r bth? What are the key pririties n technlgies gaps (Grund and On-Bard)? D we need grund simulatrs and/r in-rbit demnstratrs? Will AI and Machine Learning be injected everywhere in Space Systems? Which type f Cperatin / Spin-in with ther transprtatin dmains : Autmtive, UAV, Aircraft, Railway.? Can we insure Safety/Quality bjectives and standards n Autnmus Systems develpment? 6

7 STRENGTHS - xxxx AUTONOMY & OPERATIONS T be elabrated WEAKNESSES - xxxxx OPPORTUNITIES - xxxxx THREATS - xxxxx 7