Rover Autonomy

Rover Autonomy

Surrey Rover Autonomy Software and Hardware Testbed (SMART) compilation of videos

Andy Shaw from Scisys and Elie Allouis from Astrium are testing Bridget rover in a difficult Mars analogue terrain in full autonomous navigation mode for the first time. No instruments are mounted on Bridget at the moment this is purely a test of navigation and locomotion.

RI Seminar: Tara Estlin
Senior Member, Artificial Intelligence Group, Jet Propulsion Laboratory

The Autonomous Exploration for Gathering Increased Science (AEGIS) system enables automated data collection by planetary rovers. AEGIS software was uploaded to the Mars Exploration Rover (MER) mission’s Opportunity rover in December 2009 and has successfully demonstrated automated onboard targeting based on scientist-specified objectives. Prior to AEGIS, geological targets for rover remote-sensing instruments, were selected through manual analysis of imagery that was transmitted back to the operations team on Earth. AEGIS represents a significant paradigm shift — by using onboard data analysis techniques, the AEGIS software selects high-quality science targets with no human in the loop. This approach allows the rover to autonomously select and sequence targeted observations in an opportunistic fashion, which is particularly promising for narrow field-of-view instruments (such as the MER Mini-TES spectrometer and the 2011 Mars Science Laboratory (MSL) Mission ChemCam Spectrometer). This talk will provide an overview of the AEGIS automated targeting capability and describe how it is currently being used onboard the MER mission Opportunity rover.

Ocean Sciences the world over is at a cusp, with a move from the Expeditionary to the Observatory mode of doing science. Recent policy decisions in the United States, are pushing the technology for persistent observation and sampling which hitherto had been either economically unrealistic or unrealizable due to technical constraints. With the advent of ocean observatories, a number of key technologies have however proven to be promising for sustained ocean presence. In this context robots will need to be contextually aware and respond rapidly to evolving phenomenon, especially in coastal waters due to the diversity of atmospheric, oceanographic and land-sea interactions not to mention the societal impact they have on coastal communities. They will need to respond by exhibiting scientific opportunism while being aware of their own limitations in the harsh oceanic environment. Current robotic platforms however have inherent limitations; pre-defined sequences of commands are used to determine what actions the robot will perform and when irrespective of the context. As a consequence not only can the robot not recover from unforeseen failure conditions, but they’re unable to significantly leverage their substantial onboard assets to enable scientific discovery

For decades, our lives have depended on the safe operation of automated mechanisms around and inside us. The autonomy and complexity of these mechanisms is increasing dramatically. Autonomous systems such as self-driving cars rely heavily on inductive inference and on complex software, both of which confound traditional software-safety techniques that are focused on amassing sufficient confirmatory evidence to support safety claims. In this talk I survey methods and tools that, taken together, can enable a new and more productive philosophy for software safety that is based on Karl Popper’s idea of falsificationism

Magellium is an SME of 145 employees created in 2003 and specialized in the field of imagery. The Department “Perception and Robotics” leads activities in mobile robotics, especially for planetary exploration (CNES, ESA). Its activities cover a broad range of topics, from stereovision systems design until environment 3D modeling, passing by rover control and multi-robot cooperation. Its skills in visual based localisation are applied to mobile robots localisations and in the field of augmented reality.