24 citations · 27 across the 6 of their papers we have counts for
5 papers · 1 filter
Epistemic Uncertainty Aware Semantic Localization and Mapping for Inference and Belief Space Planning
Vladimir Tchuiev, Vadim Indelman
We investigate the problem of autonomous object classification and semantic SLAM, which in general exhibits a tight coupling between classification, metric SLAM and planning under…
iX-BSP: Incremental Belief Space Planning
Elad I. Farhi, Vadim Indelman
Deciding what's next? is a fundamental problem in robotics and Artificial Intelligence. Under belief space planning (BSP), in a partially observable setting, it involves calculatin…
Distributed Consistent Multi-Robot Semantic Localization and Mapping
Vladimir Tchuiev, Vadim Indelman
We present an approach for multi-robot consistent distributed localization and semantic mapping in an unknown environment, considering scenarios with classification ambiguity, wher…
General Purpose Incremental Covariance Update and Efficient Belief Space Planning via Factor-Graph Propagation Action Tree
Dmitry Kopitkov, Vadim Indelman
Fast covariance calculation is required both for SLAM (e.g.~in order to solve data association) and for evaluating the information-theoretic term for different candidate actions in…
Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping
Xinyan Yan, Vadim Indelman, Byron Boots
Recent work on simultaneous trajectory estimation and mapping (STEAM) for mobile robots has found success by representing the trajectory as a Gaussian process. Gaussian processes c…