Mars exploration rover surface operations: driving opportunity at Meridiani Planum

Since landing on the Meridiani Planum region of Mars in January 2004, the Mars exploration rover (MER) vehicle named Opportunity has been sending back pictures taken from several different craters that would provide evidence that the region did indeed have a watery past. This paper details the experience of driving Opportunity through this alien landscape during its first 400 days on Mars, from the point of view of the other rover planners, the people who tell the rover where to drive and how to use its robotic arm.     

Terrain‐adaptive wheel speed control on the Curiosity Mars rover: Algorithm and flight results

NASA's Mars Science Laboratory Curiosity rover landed in August 2012 and began experiencing higher rates of wheel damage beginning in October 2013. While the wheels were designed to accumulate considerable damage, the unexpected damage rate raised concerns regarding wheel lifetime. In response, the Jet Propulsion Laboratory developed and deployed mobility flight software on Curiosity that reduces the forces on the wheels. The new algorithm adapts each wheel's speed to fit the terrain topography in real time, by leveraging the rover's measured attitude rates and rocker/bogie suspension angles and rates. Together with a rigid‐body kinematics model, it estimates the real‐time wheel‐terrain contact angles and commands idealized, no‐slip wheel angular rates. In addition, free‐floating “wheelies” are detected and autonomously corrected. Ground test data indicate that the forces on the wheels are reduced by 19% for leading wheels and 11% for middle leading wheels. On the ground, the required data volume increased by up to 129%, and drive duration increased by up to 25%. In flight, data collected over 3.6 km and 149 drives confirmed a reduction in wheel current, correlated with wheel torque, of 18.7%. The new algorithm proved to use fewer resources in flight than ground estimates suggested, as only a 10% increase in drive duration and double the drive data volume were experienced. These data indicate the promise of the new algorithm to extend the life of the wheels for the Curiosity rover. This paper describes the algorithm, its ground testing campaign and associated challenges, and its validation, implementation, and performance in flight.     

Automatic detection of dust devils and clouds on Mars

The acquisition of science data in space applications is shifting from teleoperated data collection to an automated onboard analysis, resulting in improved data quality, as well as improved usage of limited resources such as onboard memory, CPU, and communications bandwidth. Science instruments onboard a modern deep-space spacecraft can acquire much more data that can be downloaded to Earth, given the limited communication bandwidth. Onboard data analysis offers a means of compressing the huge amounts of data collected and downloading only the most valuable subset of the collected data. In this paper, we describe algorithms for detecting dust devils and clouds onboard Mars rovers, and summarize the results. These algorithms achieve the accuracy required by planetary scientists, as well as the runtime, CPU, memory, and bandwidth constraints set by the engineering mission parameters. The detectors have been uploaded to the Mars Exploration Rovers, and currently are operational. These detectors are the first onboard science analysis processes on Mars.