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Robot Navigation

26 papers with code · Robots

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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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

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

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

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 ROBOT NAVIGATION

Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation

29 Sep 2017gkahn13/gcg

To address the need to learn complex policies with few samples, we propose a generalized computation graph that subsumes value-based model-free methods and model-based methods, with specific instantiations interpolating between model-free and model-based.

Q-LEARNING ROBOT NAVIGATION

Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environments

28 May 2020RoblabWh/RobLearn

In this paper we present our proof of concept for autonomous self-learning robot navigation in an unknown environment for a real robot without a map or planner.

CONTINUOUS CONTROL ROBOT NAVIGATION

CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description

6 Jan 2020SRainGit/CAE-LO

As an important technology in 3D mapping, autonomous driving, and robot navigation, LiDAR odometry is still a challenging task.

AUTONOMOUS DRIVING INTEREST POINT DETECTION ROBOT NAVIGATION