Academia.eduAcademia.edu

Outline

Title
Abstract
Figures
Introduction
Goda: Scientific Data Analysis
Testing and Validation. Use Cases
Ergo Use Case: Planetary Mission
Ergo Use Case: Orbital Mission
References

The ERGO framework and its use in planetary/orbital scenarios

Profile image of T. KellerT. KellerProfile image of Jorge OconJorge Ocon

2018

Abstract

ERGO (European Robotic Goal-Oriented Autonomous Controller) [1] is one of the six space robotic projects in the frame of the first call of the PERASPERA SRC. ERGO is aimed to future space missions, in which space robots will require a higher level of autonomy (e.g. Exomars or Mars2020). As a framework, ERGO provides a set of components that can be reused and tailored for robots space missions (Orbital, Deep Space or Planetary Explorations) in which the on-board system has to work autonomously, performing complex operations in hazardous environments without human intervention. The concept of autonomy can be applied to a whole set of operations to be performed on-board with no human supervision, such as Martian exploration rovers, deep space probes, or inorbit assembly robots. In the last decades, the advantages of increasing the level of autonomy in spacecraft have been demonstrated in planetary rovers. At the same time, orbital space missions have already successfully applied autono...

Figures (9)
Figure 1: ERGO Framework packages
Figure 1: ERGO Framework packages
Figure 3: GODA Design Overview
Figure 3: GODA Design Overview
To give a particular example, if the GODA reactor detects an interesting rock in a wide-angle image, it may raise a goal to acquire a high-resolution image of that rock. This goal is then posted to the mission planner. If the mission planner reactor is able to find a plan that is compatible with the fulfilment of all the pending goals, the plan will be changed to accommodate these new activities, and the system will execute the required tasks to acquire the image. This interaction between GODA and the mission planner is detailed in Figure 4.
To give a particular example, if the GODA reactor detects an interesting rock in a wide-angle image, it may raise a goal to acquire a high-resolution image of that rock. This goal is then posted to the mission planner. If the mission planner reactor is able to find a plan that is compatible with the fulfilment of all the pending goals, the plan will be changed to accommodate these new activities, and the system will execute the required tasks to acquire the image. This interaction between GODA and the mission planner is detailed in Figure 4.
integrated in the TASTE GUI. The generated C++ FDIR component can be easily integrated in a TASTE design by writing the suitable communication wrappers. Figure 5: System design process in the context of the BIP framework.
integrated in the TASTE GUI. The generated C++ FDIR component can be easily integrated in a TASTE design by writing the suitable communication wrappers. Figure 5: System design process in the context of the BIP framework.
Figure 6: The rover guidance includes (in blue): building of a navigation map, path planning, hazard prevention, trajectory control and resources estimation
Figure 6: The rover guidance includes (in blue): building of a navigation map, path planning, hazard prevention, trajectory control and resources estimation
The modes are designed as layers, where the higher mode level encompasses the functions of the lower modes, as seen on Figure 7. The higher the mode number, the more planning, mapping and complexity is included, and therefore the computation takes longer leading to slower rover progress. Figure 7: Possible Rover Guidance Modes which incrementally incorporate more complex functions
The modes are designed as layers, where the higher mode level encompasses the functions of the lower modes, as seen on Figure 7. The higher the mode number, the more planning, mapping and complexity is included, and therefore the computation takes longer leading to slower rover progress. Figure 7: Possible Rover Guidance Modes which incrementally incorporate more complex functions
Figure 8: Design of a robotic arm for an orbital mission using TASTE
Figure 8: Design of a robotic arm for an orbital mission using TASTE
The robotic platform rover from DFKI. SherpaTT is a 4-wheeled planetary exploration rover with an developed for high mobi rover is able to use energy (in contrast to distances, and at egged terrain by dynamically ada slopes and obstac being used is the SherpaTT actuated suspension system ity in irregular terrain. The efficient wheeled locomotion ocomotion) to cover long the same time to negotiate difficult pting the wheel suspension to es. SherpaTT has an overall weight around 150 kg. Due to self-locking gears in the four suspension units, additional payload the rover is able to cope with high weights without increasing energy consumption to maintain the current robot’s body pose. The following figure shows the SherpaTT rover while being tested at DF KT facilities
The robotic platform rover from DFKI. SherpaTT is a 4-wheeled planetary exploration rover with an developed for high mobi rover is able to use energy (in contrast to distances, and at egged terrain by dynamically ada slopes and obstac being used is the SherpaTT actuated suspension system ity in irregular terrain. The efficient wheeled locomotion ocomotion) to cover long the same time to negotiate difficult pting the wheel suspension to es. SherpaTT has an overall weight around 150 kg. Due to self-locking gears in the four suspension units, additional payload the rover is able to cope with high weights without increasing energy consumption to maintain the current robot’s body pose. The following figure shows the SherpaTT rover while being tested at DF KT facilities
Table 2: Preliminary and field tests - ERGO planetary
Table 2: Preliminary and field tests - ERGO planetary

Related papers

Autonomy in space: Current capabilities and future challenge
Liam Pedersen

■ This article provides an overview of the nature and role of autonomy for space exploration, with a bias in focus towards describing the relevance of AI technologies. It explores the range of autonomous behavior that is relevant and useful in space exploration and illustrates the range of possible behaviors by presenting four case studies in space-exploration systems, each differing from the others in the degree of autonomy exemplified. Three core requirements are defined for autonomous space systems, and the architectures for integrating capabilities into an autonomous system are described. The article concludes with a discussion of the challenges that are faced currently in developing and deploying autonomy technologies for space.

View PDFchevron_right
Towards Autonomous Planetary Exploration
Armin Wedler

Journal of Intelligent & Robotic Systems, 2017

Planetary exploration poses many challenges for a robot system: From weight and size constraints to extraterrestrial environment conditions, which constrain the suitable sensors and actuators. As the distance to other planets introduces a significant communication delay, the efficient operation of a robot system requires a high level of autonomy. In this work, we present our Lightweight Rover Unit (LRU), a small and agile rover prototype that we designed for the challenges of planetary exploration. Its locomotion system with individually steered wheels allows for high maneuverability in rough terrain and stereo cameras as its main sensors ensure the applicability to space missions. We implemented software components for self-localization This work was supported by the Helmholtz Association, project alliance ROBEX (contract number HA-304) and partially funded by the DLR Space Administration.

View PDFchevron_right
Ergo:A Framework for the Development of Autonomous Robots
Jorge Ocon

2017

If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections.

View PDFchevron_right
Advanced Technologies for Robotic Exploration Leading to Human Exploration (Results from SpaceOps 2015 Workshop).pptx
Mark L. Lupisella
View PDFchevron_right
A Goal-oriented Autonomous Controller for Space Exploration
Simone Fratini

2011

The Autonomous Controller is an on-going activity at ESA ESTEC. The Goal-Oriented Autonomous Controller (GOAC) that will eventually result as an outcome of this activity is envisaged in the frame of future ESA missions wherein on-board autonomy is important. The GOAC is an autonomous controller using a sense-planact paradigm to provide increasing levels of autonomy for robotic task achievement. GOAC will generate plans in situ, deterministically dispatch activities for execution, and recover from off-nominal conditions.

View PDFchevron_right
Spacecraft Autonomy Challenges for Next-Generation Space Missions
Issa Nesnas

Advances in Control System Technology for Aerospace Applications, 2015

In early 2011, NASA's Office of the Chief Technologist released a set of technology roadmaps with the aim of fostering the development of concepts and cross-cutting technologies addressing NASA's needs for the 2011-2021 decade and beyond. NASA reached out to the National Research Council (NRC) to review the program objectives and prioritize their list of technologies. In January 2012, the NRC released its report entitled "Restoring NASA's Technological Edge and Paving the Way for a New Era in Space." While the NRC report provides a systematic and thorough ranking of the future technology needs for NASA, it does not discuss in detail the technical aspects of the prioritized technologies (that is clearly beyond the scope of the report). This chapter, building upon the NRC report, aims at providing technical details for a selected number of high-priority technologies in the autonomous systems area. Specifically, this chapter focuses on technology area TA04 "Robotics, Tele-Robotics, and Autonomous Systems" and discusses in some detail the technical aspects and challenges associated with three high-priority TA04 technologies: "Relative Guidance Algorithms", "Extreme Terrain Mobility", and "Small Body/Microgravity Mobility." Each of these technologies is discussed along four main dimensions: scope, need, state of the art, and challenges and future directions. The result is a unified explanation of key autonomy challenges for next generation space missions.

View PDFchevron_right
Operations for Autonomous Spacecraft
Rashied Amini

ArXiv, 2021

Onboard autonomy technologies such as planning and scheduling, identification of scientific targets, and content-based data summarization, will lead to exciting new space science missions. However, the challenge of operating missions with such onboard autonomous capabilities has not been studied to a level of detail sufficient for consideration in mission concepts. These autonomy capabilities will require changes to current operations processes, practices, and tools. We have developed a case study to assess the changes needed to enable operators and scientists to operate an autonomous spacecraft by facilitating a common model between the ground personnel and the onboard algorithms. We assess the new operations tools and workflows necessary to enable operators and scientists to convey their desired intent to the spacecraft, and to be able to reconstruct and explain the decisions made onboard and the state of the spacecraft. Mock-ups of these tools were used in a user study to underst...

View PDFchevron_right
Space Robotics
Alex Ellery

International Journal of Advanced Robotic Systems, 2004

View PDFchevron_right
Model-Based Autonomy for the Next Generation of Robotic Spacecraft
L. Fesq

2002

A novel approach to the design of reactive embedded software systems, called model-based autonomy, is generating significant interest in the space systems community. The goal of the model-based approach is to automate onboard sequence execution by tightly integrating goal-driven commanding with fault detection, diagnosis, and recovery capabilities. This paper describes Titan, a system-level autonomy framework that expands upon previous model-based approaches to configuration management, such as the Livingstone mode identification and reconfiguration system, which was demonstrated on the Deep Space One spacecraft. Titan is a model-based executive that estimates current spacecraft modes, detects and repairs failures, and executes commands, all within a fast sense-decide-act loop. This paper discusses the model-based software technologies implemented within the Titan executive. It describes a case study of the deployment of Titan to a representative space mission, including an overview...

View PDFchevron_right
Autonomous Science on the EO-1 Mission
Stephen Ungar

… Symposium on Artificial …, 2003

Appears in Proceedings of International Symposium on Artificial Intelligence Robotics and Automation in Space (i-SAIRAS), Nara, Japan, May 2003. Autonomous Science on the EO-1 Mission ... Steve Chien, Rob Sherwood, Daniel Tran, Rebecca Castano, Benjamin Cichy, Ashley Davies, ...

View PDFchevron_right

References (26)

  1. ERGO web site: http://www.h2020-ergo.eu/
  2. M. Perrotin, J.-L. Terraillon, C. Honvault Taste: towards a space system development framework, Oct. 2015
  3. ECSS Secretariat. (ESA/ESTEC), "ECSS-E-70-11 Space Segment Operability" (August, 2005)
  4. J. Benton, A. J. Coles, A. I. Coles, Temporal Planning with Preferences and Time-Dependent Continuous Costs, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2012
  5. P. Eyerich, R Mattmüller, G. Röger, Using the Context-enhanced Additive Heuristic for Temporal and Numeric Planning, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2009
  6. M. Fox, D Long, PDDL2.1: An Extension of PDDL Copyright ©2018 by the International Astronautical Federation (IAF). All rights reserved. IAC-18.D1.6.12x46215 Page 13 of 13
  7. for Expressing Temporal Planning Domain, Journal of AI Research 20 (2003)
  8. G. Paar, M. Woods, C. Gimkiewicz, F. Labrosse, A. Medina, L. Tyler, D. P. Barnes, G. Fritz, and K. Kapellos, "PRoViScout: a planetary scouting rover demonstrator," Proc SPIE 8301 Intell. Robots Comput. Vis. XXIX Algorithms Tech., p. 83010A- 83010A-14, 2012.
  9. I. Wallace, M. Woods, "MASTER: A Mobile Autonomous Scientist for Terrestrial and Extra- Terrestrial Research, 13th Symposium on Advanced Space Technologies in Robotics and Automation, ASTRA 2015
  10. A. Ceballos S. Bensalem, A. Cesta, L. de Silva, S. Fratini, F. Ingrand, J. Ocón. Orlandini, F. Py, K. Rajan, R. Rasconi, and M. van Winnendael, Bensalem, S., , "A Goal-Oriented Autonomous Controller for space exploration
  11. J. Ocón, J. M. Delfa, T. de la Rosa, A. Garcia, Y. Escudero, GOTCHA: An Autonomous Controller for the Space Domain, Proceedings of the Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA), 2017
  12. T-REX: A model-based architecture for AUV control. C McGann, F Py, K Rajan, H Thomas, R Henthorn, R McEwen. 3rd Workshop on Planning and Plan Execution for Real-World Systems 2007
  13. A. Basu, M. Bozga, J. Sifakis, Modeling Heterogeneous Real-Time Components in BIP. In Fourth IEEE International Conference on Software Engineering and Formal Methods (SEFM) 2006, IEEE, 2006, pp. 3 -12
  14. S. Bensalem, F. Ingrand, J. Sifakis, Autonomous Robot Software Design Challenge. In 6 th IARP/IEEE-RAS/EURON Joint Workshop on Technical Challenge for Dependable Robots in Human Environments, 2008
  15. A. Basu, M. Gallien, C. Lesire, T. Nguyen, S. Bensalem, F. Ingrand, J. Sifakis, Incremental Component-Based Construction and Verification of a Robotic System. In European Conference on Artificial Intelligence (ECAI) 2008, IOS Press, volume 178 of FAIA, pp. 631 -635
  16. C. Backström, B. Nebel, Complexity Results for SAS+ Planning, Computational Intelligence 11 (1995)
  17. J. Hoffmann, B. Nebel, The FF Planning System: Fast Plan Generation Through Heuristic Search, Journal of AI Research 14 (2001)
  18. A. J. Coles, A. I. Coles, M. Fox, D. Long, Extending the Use of Inference in Temporal Planning as Forwards Search", Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2009
  19. K. Tierney, A. J. Coles, A. I. Coles, C. Kroer, A. Britt, R. M. Jensen, Automated Planning for Liner Shipping Fleet Repositioning.", Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2012
  20. C. Dornhege, P.Eyerich, T.Keller, S.Trüg, M.Brenner, B.Nebel, Semantic Attachments for Domain-Independent Planning Systems, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2009
  21. J. Rintanen, Complexity of Concurrent Temporal Planning, Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2007
  22. I. Dragomir, S. Iosti, M. Bozga, S. Bensalem, Designing Systems with Detection and Reconfiguration Capabilities: a Formal Approach. In 8th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation (ISOLA) 2018, Springer
  23. M. Winter et al., "ExoMars Rover Vehicle: Detailed Description of the GNC System", Proceedings of Space Technologies in Robotics and Automation (ASTRA), Noordwijk, The Netherlands, 2015, 11-13 May.
  24. J. J. Biesiadecky et al, The Mars Exploration Rover Surface Mobility Flight Software: Driving Ambition, IEEE Aerospace Conference Proceedings, 2006
  25. James J. Kuffner, Jr., Steven M. LaValle "RRT- Connect: An Efficient Approach to Single-Query Path Planning". In Proc. 2000 IEEE Int'l Conf. on Robotics and Automation (ICRA 2000)
  26. M. Muñoz et al; ESROCOS: a robotic operating system for space and terrestrial applications. (2017) In: 14th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA 2017), 20 June 2017 -21 June 2017 (Scheltema, Netherlands)

Related papers

Esrocos: A Robotic Operating System for Space and Terrestrial Applications
Ali Ado Muhammad

2017

ESROCOS (http://www.h2020-esrocos.eu) is a European Project in the frame of the PERASPERA SRC, (http://www.h2020-peraspera.eu/), targeting the design of a Robot Control Operating Software (RCOS) for space robotics applications. The goal of the ESROCOS project is to provide an open-source framework to assist in the development of flight software for space robots, providing adequate features and performance with space-grade Reliability, Availability, Maintainability and Safety (RAMS) properties. This paper presents the ESROCOS project and summarizes the approach and the current status.

View PDFchevron_right
Autonomy for Space Robots: Past, Present, and Future
Issa Nesnas

Current Robotics Reports, 2021

Purpose of Review The purpose of this review is to highlight space autonomy advances across mission phases, capture the anticipated need for autonomy and associated rationale, assess state of the practice, and share thoughts for future advancements that could lead to a new frontier in space exploration. Recent Findings Over the past two decades, several autonomous functions and system-level capabilities have been demonstrated and used in spacecraft operations. In spite of that, spacecraft today remain largely reliant on ground in the loop to assess situations and plan next actions, using pre-scripted command sequences. Advances have been made across mission phases including spacecraft navigation; proximity operations; entry, descent, and landing; surface mobility and manipulation; and data handling. But past successful practices may not be sustainable for future exploration. The ability of ground operators to predict the outcome of their plans seriously diminishes when platforms phy...

View PDFchevron_right
Architecture and tools for autonomy in space
Malik Ghallab

2001

The LAAS 1 architecture has been developed over the years in a robotic context, to control autonomous robots from the low level control loop up to the mission planning and task execution. It defines a consistent set of methods and tools to enable and ease the integration of such diverse treatments. Similarities between the robotics domain and the space domain seem to indicate that, after being used on mobile robots, the LAAS architecture could now be used onboard satellites and autonomous spacecraft. In particular, we present in detail two components of the architecture which are particularly critical to the space domain: the Faults Detection/Protection system, and the Planning module. For these two components, we also briefly present ongoing works and researches to extend and improve the existing tools and approaches.

View PDFchevron_right
A Robot Supervision Architecture for Safe and Efficient Space Exploration and Operation
Ehud Halberstam

Proc. 10th Biennial Int'l …, 2006

Current NASA plans envision human beings returning to the Moon in 2018 and, once there, establishing a permanent outpost from which we may initiate a long-term effort to visit other planetary bodies in the Solar System. This will be a bold, risky, and costly journey, comparable to the Great Navigations of the fifteenth and sixteenth centuries. Therefore, it is important that all possible actions be taken to maximize the astronauts' safety and productivity. This can be achieved by deploying fleets of autonomous robots for mineral prospecting and mining, habitat construction, fuel production, inspection and maintenance, etc.; and by providing the humans with the capability to telesupervise the robots' operation and to teleoperate them whenever necessary or appropriate, all from a safe, "shirtsleeve" environment.

View PDFchevron_right
Experiments with Autonomous Software for Planetary Robots: A Simulation Success Story
Lorenzo Flueckiger

I Sairas 2005 the 8th International Symposium on Artificial Intelligence Robotics and Automation in Space, 2005

Autonomy is a key enabling factor for robotic exploration. There continues to be a large gap between autonomy software at the research level and software that is ready for insertion into near-term space missions. The Mission Simulation Facility (MSF) project attempts to bridge this gap by providing a simulation framework and a suite of tools to support research and maturation of autonomy. The MSF has a proven track record in developing applications for simulated surface planetary missions. Moreover, the innovative framework is readily adaptable to a large range of missions by providing a modular architecture and a mixed-fidelity simulation. This paper first describes the requirements for effective autonomy software development and then presents technology developed to this model that resulted in the Mission Simulation Toolkit (MST). It further shows how this toolkit was applied to several projects and the lessons learned during the process. Finally, future directions and applications are presented.

View PDFchevron_right
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved