Robot Navigation
130 papers with code • 4 benchmarks • 14 datasets
The fundamental objective of mobile Robot Navigation is to arrive at a goal position without collision. The mobile robot is supposed to be aware of obstacles and move freely in different working scenarios.
Libraries
Use these libraries to find Robot Navigation models and implementationsDatasets
Most implemented papers
Correlation Flow: Robust Optical Flow Using Kernel Cross-Correlators
Robust velocity and position estimation is crucial for autonomous robot navigation.
PyRobot: An Open-source Robotics Framework for Research and Benchmarking
This paper introduces PyRobot, an open-source robotics framework for research and benchmarking.
Object Goal Navigation using Goal-Oriented Semantic Exploration
We propose a modular system called, `Goal-Oriented Semantic Exploration' which builds an episodic semantic map and uses it to explore the environment efficiently based on the goal object category.
Semantics through Time: Semi-supervised Segmentation of Aerial Videos with Iterative Label Propagation
Motivated by the lack of a large video aerial dataset, we also introduce Ruralscapes, a new dataset with high resolution (4K) images and manually-annotated dense labels every 50 frames - the largest of its kind, to the best of our knowledge.
Robot Navigation in Constrained Pedestrian Environments using Reinforcement Learning
Navigating fluently around pedestrians is a necessary capability for mobile robots deployed in human environments, such as buildings and homes.
Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning
Safe and efficient navigation through human crowds is an essential capability for mobile robots.
End-to-End Egospheric Spatial Memory
Spatial memory, or the ability to remember and recall specific locations and objects, is central to autonomous agents' ability to carry out tasks in real environments.
Detecting danger in gridworlds using Gromov's Link Condition
We initiate a study of gridworlds using the mathematical framework of reconfigurable systems and state complexes due to Abrams, Ghrist & Peterson.
Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph
We study the problem of safe and intention-aware robot navigation in dense and interactive crowds.
PlanVerb: Domain-Independent Verbalization and Summary of Task Plans
Our method can generate natural language descriptions of plans including causal explanations.