The LRU Rover for Autonomous Planetary Exploration and Its Success in the SpaceBotCamp Challenge

The task of planetary exploration poses many challenges for a robot system, from weight and size constraints to sensors and actuators suitable for extraterrestrial environment conditions. In this work, we present the Light Weight 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 the application of stereo cameras as its main sensor ensures the applicability to space missions. We implemented software components for self-localization in GPS-denied environments, environment mapping, object search and localization and for the autonomous pickup and assembly of objects with its arm. Additional high-level mission control components facilitate both autonomous behavior and remote monitoring of the system state over a delayed communication link. We successfully demonstrated the autonomous capabilities of our LRU at the SpaceBotCamp challenge, a national robotics contest with focus on autonomous planetary exploration. A robot had to autonomously explore a moon-like rough-terrain environment, locate and collect two objects and assemble them after transport to a third object - which the LRU did on its first try, in half of the time and fully autonomous.

[1]  Keith Golden,et al.  Autonomous rovers for Mars exploration , 1999, 1999 IEEE Aerospace Conference. Proceedings (Cat. No.99TH8403).

[2]  Darius Burschka,et al.  Local reference filter for life-long vision aided inertial navigation , 2014, 17th International Conference on Information Fusion (FUSION).

[3]  Zoltan-Csaba Marton,et al.  Automatic scene parsing for generic object descriptions using shape primitives , 2016, Robotics Auton. Syst..

[4]  Michael Beetz,et al.  Multi-robot 6D graph SLAM connecting decoupled local reference filters , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[5]  Alexander Beyer,et al.  Pan/Tilt-Unit as a perception module for extra-terrestrial vehicle and landing systems , 2013 .

[6]  Jörg Stückler,et al.  NimbRo Explorer: Semiautonomous Exploration and Mobile Manipulation in Rough Terrain , 2015, J. Field Robotics.

[7]  David S. Wettergreen,et al.  Long-Distance Autonomous Survey and Mapping in the Robotic Investigation of Life in the Atacama Desert , 2008 .

[8]  J. Schwender,et al.  The Artemis Rover as an Example for Model Based Engineering in Space Robotics , 2014 .

[9]  Gerd Hirzinger,et al.  Optimal Hand-Eye Calibration , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Jonathan M. Garibaldi,et al.  Fast, unconstrained camera motion estimation from stereo without tracking and robust statistics , 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

[11]  Jakob Schwendner,et al.  Mobile Payload Element (MPE): Concept study for a sample fetching rover for the ESA Lunar Lander Mission , 2012 .

[12]  Ch. Andre,et al.  Synccharts: A visual representation of reactive behaviors , 1995 .

[13]  Michael Suppa,et al.  Submap matching for stereo-vision based indoor/outdoor SLAM , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[14]  Oussama Khatib,et al.  Experimental Robotics IV, The 4th International Symposium, Stanford, California, USA, June 30 - July 2, 1995 , 1997, ISER.

[15]  Frank Dellaert,et al.  iSAM2: Incremental smoothing and mapping using the Bayes tree , 2012, Int. J. Robotics Res..

[16]  Klaus Landzettel,et al.  DLRs dynamic actuator modules for robotic space applications , 2012 .

[17]  Ronny Hartanto,et al.  Towards Coordinated Multirobot Missions for Lunar Sample Collection in an Unknown Environment , 2014, J. Field Robotics.

[18]  R. Anderson,et al.  Mars Science Laboratory Mission and Science Investigation , 2012 .

[19]  Darius Burschka,et al.  State estimation for highly dynamic flying systems using key frame odometry with varying time delays , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[20]  Bernhard Rebele,et al.  LRU – Lightweight Rover Unit , 2015 .

[21]  Michael Suppa,et al.  Stereo-vision based obstacle mapping for indoor/outdoor SLAM , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Roy Lichtenheldt,et al.  Hayabusa II – MASCOT Asteroid Lander with innovative Mobility Mechanism , 2015 .

[23]  Heiko Hirschmüller,et al.  Stereo Processing by Semiglobal Matching and Mutual Information , 2008, IEEE Trans. Pattern Anal. Mach. Intell..