Retrospectives on the embodied ai workshop
We present a retrospective on the state of Embodied AI research. Our analysis focuses on
13 challenges presented at the Embodied AI Workshop at CVPR. These challenges are …
13 challenges presented at the Embodied AI Workshop at CVPR. These challenges are …
Learning active camera for multi-object navigation
Getting robots to navigate to multiple objects autonomously is essential yet difficult in robot
applications. One of the key challenges is how to explore environments efficiently with …
applications. One of the key challenges is how to explore environments efficiently with …
Saynav: Grounding large language models for dynamic planning to navigation in new environments
Semantic reasoning and dynamic planning capabilities are crucial for an autonomous agent
to perform complex navigation tasks in unknown environments. It requires a large amount of …
to perform complex navigation tasks in unknown environments. It requires a large amount of …
Multi-Object Navigation with dynamically learned neural implicit representations
Understanding and mapping a new environment are core abilities of any autonomously
navigating agent. While classical robotics usually estimates maps in a stand-alone manner …
navigating agent. While classical robotics usually estimates maps in a stand-alone manner …
End-to-end (instance)-image goal navigation through correspondence as an emergent phenomenon
G Bono, L Antsfeld, B Chidlovskii… - arXiv preprint arXiv …, 2023 - arxiv.org
Most recent work in goal oriented visual navigation resorts to large-scale machine learning
in simulated environments. The main challenge lies in learning compact representations …
in simulated environments. The main challenge lies in learning compact representations …
Learning whom to trust in navigation: dynamically switching between classical and neural planning
Navigation of terrestrial robots is typically addressed either with localization and mapping
(SLAM) followed by classical planning on the dynamically created maps, or by machine …
(SLAM) followed by classical planning on the dynamically created maps, or by machine …
Mopa: Modular object navigation with pointgoal agents
We propose a simple but effective modular approach MOPA (Modular ObjectNav with
PointGoal agents) to systematically investigate the inherent modularity of the object …
PointGoal agents) to systematically investigate the inherent modularity of the object …
Multi-Object Navigation in real environments using hybrid policies
A Sadek, G Bono, B Chidlovskii… - … on Robotics and …, 2023 - ieeexplore.ieee.org
Navigation has been classically solved in robotics through the combination of SLAM and
planning. More recently, beyond waypoint planning, problems involving significant …
planning. More recently, beyond waypoint planning, problems involving significant …
Sequence-agnostic multi-object navigation
The Multi-Object Navigation (MultiON) task requires a robot to localize an instance (each) of
multiple object classes. It is a fundamental task for an assistive robot in a home or a factory …
multiple object classes. It is a fundamental task for an assistive robot in a home or a factory …
Autonerf: Training implicit scene representations with autonomous agents
Implicit representations such as Neural Radiance Fields (NeRF) have been shown to be
very effective at novel view synthesis. However, these models typically require manual and …
very effective at novel view synthesis. However, these models typically require manual and …