The new method could allow multi-robot teams to explore other planets autonomously and reliably

While roboticists have developed increasingly sophisticated systems in recent decades, ensuring that these systems can operate autonomously in real-world environments without accidents often proves challenging. This is especially difficult when these robots are designed for deployment in complex environments, including space and other planets.

Scientists at the University of Glasgow have recently developed a new methodology that could allow multi-rover teams to autonomously and reliably explore other planets. This method, presented in an article previously published on arXivit incorporates data derived from various sources, including image data, maps, and information collected by sensors, to plan efficient routes for the various robots in the team.

“Using a team of planetary exploration rovers to explore the Martian surface instead of a single rover could greatly expand the scientific capabilities of the mission,” Sarah Swinton, first author of the paper, told Tech Xplore. “All planetary exploration rovers must enjoy some level of autonomy, as communication latency between Earth and Mars makes it extremely difficult and time-consuming for humans to perform propulsion actions. Employing a team of rovers places further emphasis on autonomy, as the difficulty of coordinating their behavior increases for human operators. “

The primary goal of a recent study by Swinton and her collaborators was to effectively address a long-standing research problem in robotics: Efficient multi-robot autonomous planetary exploration missions. To that end, the team developed a multi-rover mission planner that allows a team of multiple rovers, small robots designed for space exploration, to explore an area of ​​the Martian surface autonomously, safely and efficiently.

“The method we proposed allows a robotic team to autonomously explore the Martian surface through two key phases: map generation and mission planning,” explained Swinton. “First, a map of the environment is created using data from the Mars Reconnaissance Orbiter. Specifically, we used data from Crater Lake, where NASA’s Perseverance rover is currently operating.”

After creating a map of the environment the rovers will explore on Mars, the team’s planner analyzes it and divides it into different areas, highlighting sections with terrain that the rovers can safely traverse. The planner then overlays a probability distribution map that highlights the likelihood that the rovers will encounter sites of scientific interest at specific locations in the environment they are exploring.

“These points could represent the rocks we want the rovers to sample,” Swinton said. “Once this map has been created, our mission planner scans the environment to identify an efficient route that will increase the probability of finding points of interest. A coordinated set of safe paths is then identified for each member of the rover team.”

The multi-rover mission planner developed by Swinton and her colleagues has several advantages over previously developed approaches. In addition to delineating the terrain the rovers can safely travel through and planning paths for their autonomous operation, the planner also provides information on where sites of scientific interest might be.

“Our rover team is able to safely and efficiently search the entire mission, which covers 22,500 m² in a relatively short period of time,” Swinton said. “It’s also worth noting that each rover will travel an autonomous distance comparable to the current record for ‘longest distance traveled without human control’ by a planetary exploration rover. Our work also showed that search efficiency was improved by using a team of rovers over a single rover.”

Swinton and her colleagues evaluated their mapping and planning approach in a series of tests and simulations using a set of randomly generated probability distribution maps. Their results were very promising, suggesting that their method could allow a team of five rovers to autonomously explore an area of ​​22,500 m² on Mars in approximately 40 minutes.

While the planner has so far been applied to Mars exploration, it could be applied to other missions outside of planetary exploration. For example, it could also help coordinate the efforts of multiple ground robots during search and rescue operations simply by using a map of the environment of interest and a probability distribution map that highlights the locations where robots are most likely to encounter people to be rescued. or who need help.

In their next studies, Swinton and her colleagues plan to further develop and test their methodology, while working on additional computational tools to support the autonomous operation of multiple robots. These tools will also include methods to improve the resilience of multi-robot teams.

“The effects of failures and failures are a serious problem in planetary exploration rovers’ missions,” Swinton added. “For a team of planetary exploration robots to be considered credible, the robots must be able to diagnose faults with themselves and/or their teammates. Only after faults are diagnosed can corrective actions be taken to mitigate any impact of the fault on the mission.” results.”

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