TY - GEN
T1 - Intelligent Rising Sprawl Tuned Autonomous Robot
AU - Siboni, Tomer
AU - Coronel, Matan
AU - Berman, Sigal
AU - Zarrouk, David
N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - Miniature crawling or driving robots have been developed in recent years for off-road tasks such as search and rescue, excavation, and reconnaissance. Their small dimensions, low weight, and high navigability enable their deployment in large numbers to quickly inspect large areas. There are some examples of palm-sized robots that we designed and created that can crawl or drive, including instances from a particular family of Sprawl-Tuned Autonomous Robots (STAR), i.e., STAR [1] and Rising-STAR [2]. These robots can actively adjust their sprawl angle to change the geometry between wheels and "whegs" in different planes. Using their unique configuration, these robots can move on varying terrain surfaces and traverse obstacles. The Rising-STAR has been simulated and examined with different types of machine learning algorithms [3, 4], to improve its abilities in different aspects.
AB - Miniature crawling or driving robots have been developed in recent years for off-road tasks such as search and rescue, excavation, and reconnaissance. Their small dimensions, low weight, and high navigability enable their deployment in large numbers to quickly inspect large areas. There are some examples of palm-sized robots that we designed and created that can crawl or drive, including instances from a particular family of Sprawl-Tuned Autonomous Robots (STAR), i.e., STAR [1] and Rising-STAR [2]. These robots can actively adjust their sprawl angle to change the geometry between wheels and "whegs" in different planes. Using their unique configuration, these robots can move on varying terrain surfaces and traverse obstacles. The Rising-STAR has been simulated and examined with different types of machine learning algorithms [3, 4], to improve its abilities in different aspects.
KW - Bio-Inspiration
KW - Reconfigurable robot
KW - Reinforcement learning
UR - http://www.scopus.com/inward/record.url?scp=85215798175&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-71301-9_7
DO - 10.1007/978-3-031-71301-9_7
M3 - Conference contribution
SN - 9783031713002
T3 - Lecture Notes in Networks and Systems
SP - 79
EP - 80
BT - Walking Robots into Real World - Proceedings of the CLAWAR 2024 Conference
A2 - Berns, Karsten
A2 - Tokhi, Mohammad Osman
A2 - Roennau, Arne
A2 - Silva, Manuel F.
A2 - Dillmann, Rüdiger
PB - Springer Science and Business Media Deutschland GmbH
T2 - 27th International Conference series on Climbing and Walking Robots and the Support Technologies for Mobile Machines, CLAWAR 2024
Y2 - 4 September 2024 through 6 September 2024
ER -