TY - GEN
T1 - Earth-Shaping with Heterogeneous Robotic Teams
T2 - 27th International Conference series on Climbing and Walking Robots and the Support Technologies for Mobile Machines, CLAWAR 2024
AU - Oliva, Federico
AU - Shaked, Tom
AU - Bar-Sinai, Karen Lee
AU - Shalev, Omer
AU - Elmakis, Oren
AU - Meles-Braverman, Ari
AU - Degani, Amir
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - This work presents an overview of autonomous earth-shaping and aggregate-forming tasks, which we address with a heterogeneous team of Unmanned Ground Vehicles equipped with shovels. Firstly, we introduce Sheperd, a Hardware In the Loop development tool integrated with ROS and physical engines like Gazebo and FlexHopper. We further address the problem of computational cost in these kinds of simulators, providing preliminary results to replace them with a probabilistic model for aggregate motion. We proceed by addressing the following major challenges: localizing the team of robots and mapping the aggregates, as well as efficient motion planning strategies. We address UGV localization and material mapping, utilizing vision-based UAV-UGV collaboration and optimization techniques for robustness. Then, we discuss motion planning, providing solutions to shape on-site material exclusively using pushing actions rather than more standard pick-and-place solutions.
AB - This work presents an overview of autonomous earth-shaping and aggregate-forming tasks, which we address with a heterogeneous team of Unmanned Ground Vehicles equipped with shovels. Firstly, we introduce Sheperd, a Hardware In the Loop development tool integrated with ROS and physical engines like Gazebo and FlexHopper. We further address the problem of computational cost in these kinds of simulators, providing preliminary results to replace them with a probabilistic model for aggregate motion. We proceed by addressing the following major challenges: localizing the team of robots and mapping the aggregates, as well as efficient motion planning strategies. We address UGV localization and material mapping, utilizing vision-based UAV-UGV collaboration and optimization techniques for robustness. Then, we discuss motion planning, providing solutions to shape on-site material exclusively using pushing actions rather than more standard pick-and-place solutions.
KW - Earth-Shaping
KW - Localization
KW - Multi-Agent
KW - Planning
UR - http://www.scopus.com/inward/record.url?scp=85206105628&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-70722-3_14
DO - 10.1007/978-3-031-70722-3_14
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AN - SCOPUS:85206105628
SN - 9783031707216
T3 - Lecture Notes in Networks and Systems
SP - 128
EP - 140
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
Y2 - 4 September 2024 through 6 September 2024
ER -