ESA Harwell Robotics & Autonomy Facility Study Workshop Autonomous Software Verification Presented By: Rick Blake

2 Robotics and Autonomy Facility Study Autonomous Software Simulation Needs

3 Robotics and Autonomy Facility Study Scope of Autonomous Systems Software Autonomous Systems technology has many diverse applications in the realm of robotic exploration including: Adaptive Planning Data Analysis and Handling Sample Collection, Processing and Analysis Navigation Resource Management Anomaly Detection, Diagnosis and Recovery Decision Making (may be distributed or involve human interaction) Sensor Exploitation – inferring knowledge from sensor data Situational Awareness - models of environment and internal state

4 Robotics and Autonomy Facility Study Simulation Needs Simulation capabilities must: Cover functional, qualification & verification testing. Encompass roving platforms, payloads and fully integrated vehicles. Be viable & useful for future robotic missions and non-space developments.

5 Robotics and Autonomy Facility Study Initial Analysis of Simulation Needs 1.Verification of declarative domain models and rules engines 2.Adjustment or mutation of the (simulated) external environment 3.Injection of combinations of faults and failures 4.Support for high speed (discrete event) simulations so that the behaviour over a long time baseline can be assessed. 5.Allow instrumentation so that behaviour is recorded accurately and in detail. 6.Provide automated analysis to process the results of a large number of high speed simulation runs. 7.Support verification of quality assurance software responsible for ‘sanity’ checking of the AS functions at run-time. 8.Support formal verification using model-checking techniques for mission critical software. 9.Support for dry runs of field trials 10.Provide a software environment or middleware combining platform, payload and environment models and simulations.

6 Robotics and Autonomy Facility Study Software Framework for AS Verification A simulation software framework and analysis toolset would: Support incremental development and testing. Enable simulation models developed for subsystems, instruments and environment to be brought together in a plug-and-play environment. Enable hardware to be seamlessly integrated into the simulations models. Reduce the time is spent integrating instrument specific simulation tools with subsystems models and commercial packages. Enable the operations and planning tools to be validated and calibrated Build confidence in the system design. Allow a distributed network of scientists and engineers to remotely participate in field trials simulations in real time Provide vital experience in operating the rover, improving the operation planning and providing a training arena for both scientists and engineers Reduce lifecycle costs by producing a robust system earlier and through more efficient validation, testing and operations.

7 Robotics and Autonomy Facility Study Other Areas of Study Adjustable autonomy to collect metrics and build confidence as the level of autonomy is varied. Support for post event analysis based on operational instrumentation of autonomy. Modelling of natural phenomena such as wind and dust. Generation of 3D environments e.g. rocks, sandtraps. Integration of hi-fidelity rover CADM models into simulated 3D environments. Use of proven AS technology from other projects to reduce risk. Integration with AISP (TRL 1-3).

8 Robotics and Autonomy Facility Study Lifecycle Support A comprehensive AS simulation environment will have a role beyond initial design and verification supporting activities such as: Verification of platform/payload software updates Design, optimisation and validation of operational procedures Incremental deployment of autonomy as trust grows. Anomaly investigation throughout the lifetime mission. Training of operations and payload teams. Design workshops. Demonstration of AS solutions that can reduce operational costs. Trials of new AS solutions on missions nearing end-of life. Space qualification of AS COTS. Develop more efficient ops concepts to address the Long Operations Tail.