Robot Navigation

61 papers with code • 4 benchmarks • 7 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.

Source: Learning to Navigate from Simulation via Spatial and Semantic Information Synthesis with Noise Model Embedding

Greatest papers with code

Online Temporal Calibration for Monocular Visual-Inertial Systems

HKUST-Aerial-Robotics/VINS-Mono 2 Aug 2018

Visual and inertial fusion is a popular technology for 6-DOF state estimation in recent years.

Autonomous Driving Robot Navigation +2

PyRobot: An Open-source Robotics Framework for Research and Benchmarking

facebookresearch/pyrobot 19 Jun 2019

This paper introduces PyRobot, an open-source robotics framework for research and benchmarking.

Robotic Grasping Robot Navigation +1

Gibson Env: Real-World Perception for Embodied Agents

StanfordVL/GibsonEnv CVPR 2018

Developing visual perception models for active agents and sensorimotor control are cumbersome to be done in the physical world, as existing algorithms are too slow to efficiently learn in real-time and robots are fragile and costly.

Domain Adaptation General Reinforcement Learning +1

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames

facebookresearch/habitat-api ICLR 2020

We leverage this scaling to train an agent for 2. 5 Billion steps of experience (the equivalent of 80 years of human experience) -- over 6 months of GPU-time training in under 3 days of wall-clock time with 64 GPUs.

Autonomous Navigation PointGoal Navigation +1

Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments

StanfordVL/iGibson 30 Oct 2019

We present Interactive Gibson Benchmark, the first comprehensive benchmark for training and evaluating Interactive Navigation: robot navigation strategies where physical interaction with objects is allowed and even encouraged to accomplish a task.

Robot Navigation

Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

vita-epfl/CrowdNav 24 Sep 2018

We propose to (i) rethink pairwise interactions with a self-attention mechanism, and (ii) jointly model Human-Robot as well as Human-Human interactions in the deep reinforcement learning framework.

Human Dynamics Human robot interaction +1

Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation

peteanderson80/Matterport3DSimulator ECCV 2018

In this paper, we take a radical approach to bridge the gap between synthetic studies and real-world practices---We propose a novel, planned-ahead hybrid reinforcement learning model that combines model-free and model-based reinforcement learning to solve a real-world vision-language navigation task.

Model-based Reinforcement Learning Robot Navigation +2

SkiMap: An Efficient Mapping Framework for Robot Navigation

m4nh/skimap_ros 19 Apr 2017

We present a novel mapping framework for robot navigation which features a multi-level querying system capable to obtain rapidly representations as diverse as a 3D voxel grid, a 2. 5D height map and a 2D occupancy grid.

Robot Navigation