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Inside a controlled Mars-like test environment, the robot moved across simulated dust and rock fields, stopping at several targets within a single run.<\/p>\n
Working in that setting, Gabriela Ligeza at the University of Basel<\/a> showed that the system could approach each target, deploy its instruments, and return meaningful scientific readings.<\/p>\n Across repeated trials, the robot consistently identified key rock types while operating without continuous input between measurements.<\/p>\n That performance establishes a faster but less supervised mode of exploration, raising the need to balance speed against precision in how future missions are planned.<\/p>\n Communication lag time<\/p>\n Earth-to-Mars messages can take up to 22 minutes one way, so communication delays<\/a> turn each new rock into another planning cycle.<\/p>\n Because teams must review data and uplink commands, traditional surface work usually advances one target at a time.<\/p>\n Instead, the new trials let scientists pick several rocks first, then let the robot walk, measure, and report back.<\/p>\n That sequence attacks rover science\u2019s slowest part, the human pause between one interesting stone and the next.<\/p>\n Cutting-edge diagnostic sensors<\/p>\n At the arm tip sat a close-up imager, while a Raman spectrometer<\/a>, a laser tool that fingerprints minerals, rode above.<\/p>\n Close views revealed cracks, grains, and textures, while Raman readings flagged mineral chemistry that appearance alone could miss.<\/p>\n Together the tools identified a range of rocks tied to water, volcanic activity, and potential resources across Mars<\/a> and Moon stand-ins.<\/p>\n That pairing mattered most when one tool stumbled, because blurred pictures or dusty surfaces did not always fool both instruments.<\/p>\n The robot delivers speed<\/p>\n Across four semi-autonomous Mars-style runs, the robot finished surveys in 12 to 23 minutes, while a guided run took 41 minutes.<\/p>\n During the best fast run, the robot identified all three chosen targets, matching the slower approach on basic success.<\/p>\n Meanwhile, the guided mission gathered more useful data because humans could inspect each result and request extra measurements.<\/p>\n That trade-off defined the core result: autonomy bought speed, while constant supervision still bought precision and higher total yield.<\/p>\n Supervision can boost detail<\/p>\n When scientists stayed in the loop after every stop, they could judge image quality and request another reading immediately.<\/p>\n In the lunar test, that freedom produced ideal close-up images for all three targets and six Raman measurements.<\/p>\n One reading came back weak, showing how mixed mineral layers can confuse compact instruments even when aiming succeeds.<\/p>\n Human review mattered less for walking than for deciding when a target deserved another try before moving on.<\/p>\n Robots on Mars need legs<\/p>\n Wheels excel on smoother routes, but many prized lunar and Martian deposits sit on steep ground where footing matters more.<\/p>\n ANYmal, a four-legged robotic platform designed for rough terrain, uses onboard sensing to map the ground and choose stable footholds while it walks.<\/p>\n That matters for future prospecting because ice, metals, or rocks that preserve life traces often lie near cliffs or slopes.<\/p>\n A faster walker that still carries science tools could scout risky places before larger missions commit power and time.<\/p>\n Targets for future missions<\/p>\n Several materials in the test were stand-ins for rocks that mission planners already care deeply about.<\/p>\n On Mars-like ground, gypsum and carbonates matter because water helped form them, making them good targets for biosignatures<\/a>, clues to past life.<\/p>\n Across lunar stand-ins, certain rocks pointed to materials that could provide oxygen or useful metals for future missions.<\/p>\n Those examples show why a quick first pass matters, since the hard part is not finding a rock but choosing well.<\/p>\n The compact gamble<\/p>\n Compact instruments usually trade depth for speed, so the real test was whether a smaller payload could still sort rocks well.<\/p>\n That problem was laid out in a Frontiers editorial<\/a> that explained the team\u2019s goal in plain language.<\/p>\n \u201cOur research question was whether a robot equipped with a simple scientific payload could quickly study several targets while still delivering meaningful scientific results,\u201d said Ligeza.<\/p>\n The result wasn\u2019t flawless accuracy at every step, but it delivered enough consistent sorting to make rapid scouting a realistic first pass.<\/p>\n Autonomous robots and Mars exploration<\/p>\n The next upgrade is not a bigger robot<\/a> but smarter checking, so it can catch blur and retake weak shots.<\/p>\n Future versions could flag targets by color, texture, or shape, then send back a short list when bandwidth is tight.<\/p>\n NASA already lets Perseverance use onboard artificial intelligence<\/a> to choose targets and drive efficiently, but not to plan a multi-target campaign.<\/p>\n One scout that can walk, inspect, and move on begins to break the stop-and-wait rhythm shaping planetary fieldwork.<\/p>\n The result does not replace slower, expert-guided science, but it offers a workable way to cover more ground.<\/p>\n The study is published in the journal Frontiers in Space Technologies<\/a>.<\/p>\n Image Credit: Dr Tomaso Bontognali<\/p>\n \u2014\u2013<\/p>\n Like what you read? Subscribe to our newsletter<\/a> for engaging articles, exclusive content, and the latest updates.<\/p>\n Check us out on EarthSnap<\/a>, a free app brought to you by Eric Ralls<\/a> and Earth.com.<\/p>\n \u2014\u2013<\/p>\n","protected":false},"excerpt":{"rendered":"Researchers have demonstrated that a legged robot can autonomously analyze multiple rocks in a single mission, completing surveys…\n","protected":false},"author":2,"featured_media":376885,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[85,46,141],"class_list":{"0":"post-376884","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-science","8":"tag-il","9":"tag-israel","10":"tag-science"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/376884","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=376884"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/376884\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/376885"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=376884"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=376884"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=376884"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}