Testing the full autonomy system in simulation is the safest and most scalable way to
evaluate autonomous vehicle performance before deployment. This requires simulating …

Conventional approaches to vision-and-language navigation (VLN) are trained end-to-end
but struggle to perform well in freely traversable environments. Inspired by the robotics …

The capacity to extract information and comprehend an unseen environment is critical for
mobile robots to navigate. Few surveys has mentioned the combinatorial-non-optimality …

The rapid progress of foundation models has led to the prosperity of autonomous agents,
which leverage the universal capabilities of foundation models to conduct reasoning …

The rapid progress of foundation models has led to the prosperity of autonomous agents,
which leverage the universal capabilities of foundation models to conduct reasoning …

When searching for objects in cluttered environments, it is often necessary to perform
complex interactions in order to move occluding objects out of the way and fully reveal the …

Offline reinforcement learning algorithms hold the promise of enabling data-driven RL
methods that do not require costly or dangerous real-world exploration and benefit from …

Embodied instruction following is a challenging problem requiring an agent to infer a
sequence of primitive actions to achieve a goal environment state from complex language …

Localization in topological maps is essential for image-based navigation using an RGB
camera. Localization using only one camera can be challenging in medium-to-large-sized …

We propose a method to facilitate robot navigation relative to sketched maps of human
environments. Our main contribution centers around using thin plate splines for registering …