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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

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Datasets

Greatest papers with code

Online Temporal Calibration for Monocular Visual-Inertial Systems

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

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

AUTONOMOUS DRIVING ROBOT NAVIGATION SENSOR FUSION TIME OFFSET CALIBRATION

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

19 Jun 2019facebookresearch/pyrobot

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

ROBOTIC GRASPING ROBOT NAVIGATION SIMULTANEOUS LOCALIZATION AND MAPPING

Gibson Env: Real-World Perception for Embodied Agents

CVPR 2018 StanfordVL/GibsonEnv

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 ROBOT NAVIGATION

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

ICLR 2020 facebookresearch/habitat-api

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 SCENE UNDERSTANDING

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

ECCV 2018 peteanderson80/Matterport3DSimulator

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.

ROBOT NAVIGATION VISION AND LANGUAGE NAVIGATION VISION-LANGUAGE NAVIGATION

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

24 Sep 2018vita-epfl/CrowdNav

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 ROBOT NAVIGATION

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

30 Oct 2019StanfordVL/iGibson

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

SkiMap: An Efficient Mapping Framework for Robot Navigation

19 Apr 2017m4nh/skimap_ros

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