A Goal-Oriented Autonomous Controller for Space Exploration

The Goal-Oriented Autonomous Controller (GOAC) is the envisaged result of a multi-institutional effort within the on-going Autonomous Controller R&D activity funded by ESA ESTEC. The objective of this effort is to design, build and test a viable on-board controller to demonstrate key concepts in fully autonomous operations for ESA missions. This three-layer architecture is an integrative effort to bring together four mature technologies; for a functional layer, a verification and validation system, a planning engine and a controller framework for planning and execution which uses the sense-plan-act paradigm for goal oriented autonomy. GOAC as a result will generate plans in situ, deterministically dispatch activities for execution, and recover from off-nominal conditions

Towards Declarative Safety Rules for Perception Specification Architectures

Agriculture has a high number of fatalities compared to other blue collar fields, additionally population decreasing in rural areas is resulting in decreased work force. These issues have resulted in increased focus on improving efficiency of and introducing autonomy in agriculture. Field robots are an increasingly promising branch of robotics targeted at full automation in agriculture. The safety aspect however is rely addressed in connection with safety standards, which limits the real-world applicability. In this paper we present an analysis of a vision pipeline in connection with functional-safety standards, in order to propose solutions for how to ascertain that the system operates as required. Based on the analysis we demonstrate a simple mechanism for verifying that a vision pipeline is functioning correctly, thus improving the safety in the overall system.Comment: Presented at DSLRob 2015 (arXiv:1601.00877

SOTER: A Runtime Assurance Framework for Programming Safe Robotics Systems

The recent drive towards achieving greater autonomy and intelligence in robotics has led to high levels of complexity. Autonomous robots increasingly depend on third party off-the-shelf components and complex machine-learning techniques. This trend makes it challenging to provide strong design-time certification of correct operation. To address these challenges, we present SOTER, a robotics programming framework with two key components: (1) a programming language for implementing and testing high-level reactive robotics software and (2) an integrated runtime assurance (RTA) system that helps enable the use of uncertified components, while still providing safety guarantees. SOTER provides language primitives to declaratively construct a RTA module consisting of an advanced, high-performance controller (uncertified), a safe, lower-performance controller (certified), and the desired safety specification. The framework provides a formal guarantee that a well-formed RTA module always satisfies the safety specification, without completely sacrificing performance by using higher performance uncertified components whenever safe. SOTER allows the complex robotics software stack to be constructed as a composition of RTA modules, where each uncertified component is protected using a RTA module. To demonstrate the efficacy of our framework, we consider a real-world case-study of building a safe drone surveillance system. Our experiments both in simulation and on actual drones show that the SOTER-enabled RTA ensures the safety of the system, including when untrusted third-party components have bugs or deviate from the desired behavior

Continuous Planning and Execution with Timelines

Planning systems need to be endowed with some additional features to cope effectively with execution: e.g., the ability to keep the plan database updated with respect to the actual feedbacks provided by the controlled system, to mention but one. In this paper, we identify a set of noteworthy planning and execution open issues relatively to the timeline-based planning approach. We address those issues presenting a domain independent deliberative system, implemented on top of the APSI-TRF, the A PSI Timeline-based Representation Framework, extended with timeline dispatching and execution-supervision capabilities so as to allow continuous planning and closed-loop re-planning activities. Some ongoing research directions are also briefly introduced

The Dag-Brucken ASRS Case Study

In 1996 an agreement was made between a well-known beverage manufacturer, Super-Cola Taiwan, (SCT) and a small Australian electrical engineering company, Dag-Brücken ASRS Pty Ltd, (DB), to provide an automated storage and retrieval system (ASRS) facility as part of SCT’s production facilities in Asia. Recognising the potential of their innovative and technically advanced design, DB was awarded a State Premiers Export Award and was a finalist in that year’s National Export Awards. The case tracks the development and subsequent implementation of the SCT ASRS project, setting out to highlight how the lack of appropriate IT development processes contributed to the ultimate failure of the project and the subsequent winding up of DB only one year after being honoured with these prestigious awards. The case provides compelling evidence of the types of project management incompetency that, from the literature, appears to contribute to the high failure rate in IT projects. For confidentiality reasons, the names of the principal parties are changed, but the case covers actual events documented by one of the project team members as part of his postgraduate studies, providing an example of the special mode of evidence collection that Yin (1994) calls ‘participant-observation’

A TGA-based Method for Safety Critical Plan Execution

Safety critical planning and execution is a crucial issue in autonomous systems. This paper proposes a methodology for controller synthesis suitable for timeline-based planning and demonstrates its effectiveness in a space domain where robustness of execution is a crucial property. The proposed approach uses Timed Game Automata (TGA) for formal modeling and the UPPAAL-TIGA model checker for controllers synthesis. An experimental evaluation is performed using a real-world control system

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures