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Biomim."],"published-print":{"date-parts":[[2026,8,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Robotics would gain by replicating the remarkable agility of arthropods in navigating complex environments. In this simulation study, we consider the control of \u2018multi-legged\u2019 systems which have 6 or more legs. Current multi-legged control strategies in robots include large black-box machine learning models, central pattern generator (CPG) networks, and open-loop feed-forward control with stability arising from the mechanics. Here we present a multi-legged control architecture for rough terrain using a segmental robot with 3 actuators for every 2 legs, which we validated in simulation for 6 to 16 legs. Segments have identical state machines, and each segment also receives input from the segment in front of it. Our design bridges the gap between\n                    <jats:bold>Walknet<\/jats:bold>\n                    -like event cascade controllers and CPG-based controllers: it tightly couples to the ground when present, but produces fictive locomotion when ground contact is missing. It may be useful as an adaptive, computationally light-weight controller for multi-legged robots, and as baseline capability for scaffolding the learning of machine learning controllers.\n                  <\/jats:p>","DOI":"10.1088\/1748-3190\/ae9261","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T22:56:17Z","timestamp":1785365777000},"page":"046040","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Walking on rough terrain with any number of legs"],"prefix":"10.1088","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3968-516X","authenticated-orcid":true,"given":"Zhuoyang","family":"Chen","sequence":"first","affiliation":[{"name":"University of Michigan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6809-3584","authenticated-orcid":true,"given":"Xinyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Michigan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2989-0356","authenticated-orcid":true,"given":"Shai","family":"Revzen","sequence":"additional","affiliation":[{"name":"University of Michigan"},{"name":"University of Michigan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,8,26]]},"reference":[{"key":"bbae9261bib1","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1023\/A:1012426720699","type":"journal-article","article-title":"Rhex: a biologically inspired hexapod runner","volume":"11","author":"Altendorfer","year":"2001","journal-title":"Auton. 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