The new method may allow multi-robot teams to explore other planets independently and reliably

While roboticists have developed increasingly sophisticated systems over the past decades, ensuring that these systems can operate autonomously in real-world environments without mishaps is often difficult. This is especially difficult when these robots are designed to be deployed in complex environments, including space and other planets.

Researchers at the University of Glasgow recently developed a new methodology that could allow teams of multiple rovers to independently and reliably explore other planets. This method was introduced in A paper Previously published on arXiv,incorporates data drawn from various sources, including ,imaging data, maps and information collected by sensors, to plan,efficient paths for the various robots in the team.

“Using a team of planetary exploration rovers to explore the surface of Mars, rather than a single rover, could significantly increase the science capabilities of the mission,” Sarah Swinton, first author on the paper, told Tech Xplore. “All planetary exploration rovers must use some level of autonomy, as the communication latency between Earth and Mars makes it very difficult and time-consuming for humans to perform command actions. Employing a team of rovers places more emphasis on autonomy, e.g. “It is increasingly difficult for human operators to coordinate their behaviors.”

The primary goal of the latest study by Swinton and her collaborators was to effectively address a long-standing research problem in robotics: the efficient handling of multi-robot autonomous planetary exploration missions. To do this, the team developed a multi-vehicle mission scheme that would allow a team of several rovers, which are small robots designed for space exploration, to autonomously, safely and efficiently explore a region of Mars' surface.

“The method we proposed enables the robot team to autonomously explore the surface of Mars through two main phases: map creation and mission planning,” Swinton explained. “First, a map of the environment is created using data from the Mars Reconnaissance Orbiter. We specifically used data from Jezero Crater, where NASA's Perseverance rover is currently operating.”

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

“These dots may represent rocks that we want spacecraft to sample,” Swinton said. “Once this map is created, our mission planner searches the environment to determine an efficient route that will increase the probability of finding points of interest. A coordinated set of safe paths is then determined for each member of the rover team.”

The multi-vehicle mission scheme developed by Swinton and her colleagues has various advantages over previously developed methods. In addition to identifying terrain where rovers can travel safely and planning paths for their autonomous operation, the chart also provides information about where sites of scientific interest could be located.

“Our rover team is able to safely and efficiently search the full mission site covering an area of ​​22,500 square metres.² “In a relatively short period of time,” Swinton said. “It is also worth noting that each rover covers a self-driving distance similar to the current record for ‘the longest distance traveled by a planetary exploration rover without human review.’” Our work also showed that search efficiency was improved by using the rover team on One rover.”

Swinton and her colleagues evaluated their mapping and planning approach in a series of tests and simulations performed 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 independently explore an area of ​​22,500 square metres.² On Mars in about 40 minutes.

While the scheme has so far been applied to Mars exploration, it could be applied to missions beyond planetary exploration. For example, it can 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 locations where robots are most likely to encounter people to be rescued or who need assistance.

In their upcoming studies, Swinton and her colleagues plan to further develop and test their methodology, while also working on other computational tools to support autonomous operation of multiple robots. These tools will also include ways to improve fault tolerance across multiple robotics teams.

“The effects of errors and failures are a serious concern in planetary exploration missions,” Swinton added. “For a team of planetary exploration robots to be considered trustworthy, the robots must be able to diagnose faults in themselves and/or their teammates. Only once faults have been diagnosed can recovery actions be taken to mitigate any impact of the fault on the mission. Results.”