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Distributed Optimization with Consensus Constraint for Multi-Robot Semantic Octree Mapping (2402.08867v1)
Published 14 Feb 2024 in cs.RO
Abstract: This work develops a distributed optimization algorithm for multi-robot 3-D semantic mapping using streaming range and visual observations and single-hop communication. Our approach relies on gradient-based optimization of the observation log-likelihood of each robot subject to a map consensus constraint to build a common multi-class map of the environment. This formulation leads to closed-form updates which resemble Bayes rule with one-hop prior averaging. To reduce the amount of information exchanged among the robots, we utilize an octree data structure that compresses the multi-class map distribution using adaptive-resolution.
- A. Asgharivaskasi and N. Atanasov, “Semantic octree mapping and Shannon mutual information computation for robot exploration,” IEEE Transactions on Robotics (TRO), 2023.
- M. Corah, C. O’Meadhra, K. Goel, and N. Michael, “Communication-efficient planning and mapping for multi-robot exploration in large environments,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1715–1721, 2019.
- P. Paritosh, N. Atanasov, and S. Martinez, “Distributed bayesian estimation of continuous variables over time-varying directed networks,” IEEE Control Systems Letters, vol. 6, pp. 2545–2550, 2022.
- Y. Tian, Y. Chang, F. Herrera Arias, C. Nieto-Granda, J. P. How, and L. Carlone, “Kimera-multi: Robust, distributed, dense metric-semantic slam for multi-robot systems,” IEEE Transactions on Robotics, vol. 38, no. 4, pp. 2022–2038, 2022.
- S. M. Shah, “Distributed optimization on Riemannian manifolds for multi-agent networks,” arXiv preprint arXiv:1711.11196, 2017.
- B. Yamauchi, “A frontier-based approach for autonomous exploration,” in IEEE International Symposium on Computational Intelligence in Robotics and Automation, 1997, pp. 146–151.