PointGoal Navigation

14 papers with code • 1 benchmarks • 2 datasets

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Use these libraries to find PointGoal Navigation models and implementations

Comparison of Model-Free and Model-Based Learning-Informed Planning for PointGoal Navigation

yimengli46/bellman_point_goal 17 Dec 2022

In this work, we compare the state-of-the-art Deep Reinforcement Learning based approaches with Partially Observable Markov Decision Process (POMDP) formulation of the point goal navigation problem.

17 Dec 2022

VER: Scaling On-Policy RL Leads to the Emergence of Navigation in Embodied Rearrangement

facebookresearch/habitat-lab 11 Oct 2022

Specifically, the Pick skill involves a robot picking an object from a table.

11 Oct 2022

Is Mapping Necessary for Realistic PointGoal Navigation?

rpartsey/pointgoal-navigation CVPR 2022

However, for PointNav in a realistic setting (RGB-D and actuation noise, no GPS+Compass), this is an open question; one we tackle in this paper.

02 Jun 2022

Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models, Benchmark and Efficient Evaluation

fpv-iplab/mid-level-fusion-nav 2 Feb 2022

All the proposed navigation models have been trained with the Habitat simulator on a synthetic office environment and have been tested on the same real-world environment using a real robotic platform.

02 Feb 2022

Realistic PointGoal Navigation via Auxiliary Losses and Information Bottleneck

nicogrande/habitat-pointnav-via-ib 17 Sep 2021

Under this setting, the agent incurs a penalty for using this privileged information, encouraging the agent to only leverage this information when it is crucial to learning.

17 Sep 2021

Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI

facebookresearch/habitat-challenge 16 Sep 2021

When compared to existing photorealistic 3D datasets such as Replica, MP3D, Gibson, and ScanNet, images rendered from HM3D have 20 - 85% higher visual fidelity w. r. t.

16 Sep 2021

Out of the Box: Embodied Navigation in the Real World

aimagelab/LoCoNav 12 May 2021

In this work, we detail how to transfer the knowledge acquired in simulation into the real world.

12 May 2021

Large Batch Simulation for Deep Reinforcement Learning

shacklettbp/bps-nav ICLR 2021

We accelerate deep reinforcement learning-based training in visually complex 3D environments by two orders of magnitude over prior work, realizing end-to-end training speeds of over 19, 000 frames of experience per second on a single GPU and up to 72, 000 frames per second on a single eight-GPU machine.

12 Mar 2021

Auxiliary Tasks Speed Up Learning PointGoal Navigation

joel99/habitat-pointnav-aux 9 Jul 2020

PointGoal Navigation is an embodied task that requires agents to navigate to a specified point in an unseen environment.

09 Jul 2020

Learning to Explore using Active Neural SLAM

devendrachaplot/Neural-SLAM ICLR 2020

The use of learning provides flexibility with respect to input modalities (in the SLAM module), leverages structural regularities of the world (in global policies), and provides robustness to errors in state estimation (in local policies).

10 Apr 2020