A survey on deep learning for localization and map**: Towards the age of spatial machine intelligence

C Chen, B Wang, CX Lu, N Trigoni… - ar** has recently attracted significant attention.
Instead of creating hand-designed algorithms through exploitation of physical models or …

Scene memory transformer for embodied agents in long-horizon tasks

K Fang, A Toshev, L Fei-Fei… - Proceedings of the …, 2019 - openaccess.thecvf.com
Many robotic applications require the agent to perform long-horizon tasks in partially
observable environments. In such applications, decision making at any step can depend on …

Automatic differentiation of programs with discrete randomness

G Arya, M Schauer, F Schäfer… - Advances in Neural …, 2022 - proceedings.neurips.cc
Automatic differentiation (AD), a technique for constructing new programs which compute
the derivative of an original program, has become ubiquitous throughout scientific …

Differentiable particle filtering via entropy-regularized optimal transport

A Corenflos, J Thornton… - International …, 2021 - proceedings.mlr.press
Particle Filtering (PF) methods are an established class of procedures for performing
inference in non-linear state-space models. Resampling is a key ingredient of PF necessary …

Glas: Global-to-local safe autonomy synthesis for multi-robot motion planning with end-to-end learning

B Riviere, W Hönig, Y Yue… - IEEE robotics and …, 2020 - ieeexplore.ieee.org
We present GLAS: Global-to-Local Autonomy Synthesis, a provably-safe, automated
distributed policy generation for multi-robot motion planning. Our approach combines the …

Invigorate: Interactive visual grounding and gras** in clutter

H Zhang, Y Lu, C Yu, D Hsu, X Lan, N Zheng - ar**: A survey
C Chen, B Wang, CX Lu, N Trigoni… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep-learning-based localization and map** approaches have recently emerged as a
new research direction and receive significant attention from both industry and academia …