Robot Navigation

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

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 301–310 of 542 papers

Title	Date	Tasks	Status
KDSalBox: A toolbox of efficient knowledge-distilled saliency models	Oct 12, 2021	Image CompressionRobot Navigation	—Unverified
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning	Oct 12, 2021	Multi-agent Reinforcement LearningQ-Learning	—Unverified
Human-Aware Robot Navigation via Reinforcement Learning with Hindsight Experience Replay and Curriculum Learning	Oct 9, 2021	Decision MakingReinforcement Learning (RL)	—Unverified
3D-MOV: Audio-Visual LSTM Autoencoder for 3D Reconstruction of Multiple Objects from Video	Oct 5, 2021	3D geometry3D Reconstruction	—Unverified
Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration	Sep 29, 2021	Multi-agent Reinforcement LearningQ-Learning	—Unverified
Hierarchies of Planning and Reinforcement Learning for Robot Navigation	Sep 23, 2021	reinforcement-learningReinforcement Learning	—Unverified
Decentralized Global Connectivity Maintenance for Multi-Robot Navigation: A Reinforcement Learning Approach	Sep 17, 2021	Navigatereinforcement-learning	—Unverified
Open-World Distributed Robot Self-Localization with Transferable Visual Vocabulary and Both Absolute and Relative Features	Sep 9, 2021	Graph Neural NetworkRobot Navigation	—Unverified
Model-based Chance-Constrained Reinforcement Learning via Separated Proportional-Integral Lagrangian	Aug 26, 2021	reinforcement-learningReinforcement Learning (RL)	—Unverified
Reinforcement Learning for Robot Navigation with Adaptive Forward Simulation Time (AFST) in a Semi-Markov Model	Aug 13, 2021	Deep Reinforcement Learningreinforcement-learning	CodeCode Available

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All datasets Habitat 2020 Object Nav minival Habitat 2020 Object Nav test-std Habitat 2020 Point Nav test-std Habitat 2020 Point Nav minival

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SemExp	SPL	0.25	—	Unverified
2	SRCB-robot-sudoer	SPL	0.12	—	Unverified
3	Active Exploration (Pre-explore )	SPL	0.11	—	Unverified
4	Blue Ox	SPL	0.11	—	Unverified
5	RL	SPL	0.06	—	Unverified
6	Habitat-Web	SPL	0.03	—	Unverified
7	Objects In Mirror Are Closer Than They Appear	SPL	0	—	Unverified
8	Casa	SPL	0	—	Unverified
9	PPO RGBD	SPL	0	—	Unverified
10	Black Sheep	SPL	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	THDA	SPL	0.09	—	Unverified
2	6-Act Tether	SPL	0.08	—	Unverified
3	SRCB-robot-sudoer	SPL	0.07	—	Unverified
4	SemExp	SPL	0.07	—	Unverified
5	Active Exploration (Pre-explore )	SPL	0.04	—	Unverified
6	RGBD+DD-PPO	SPL	0.02	—	Unverified
7	RL_20_torch_18	SPL	0.02	—	Unverified
8	Blue Ox	SPL	0.02	—	Unverified
9	Black Sheep	SPL	0	—	Unverified
10	RandomAgent	SPL	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VO	SPL	0.53	—	Unverified
2	SLAM-net + D*	SPL	0.38	—	Unverified
3	OccupancyAnticipation	SPL	0.22	—	Unverified
4	Information Bottleneck	SPL	0.12	—	Unverified
5	ego-localization	SPL	0.12	—	Unverified
6	39	SPL	0.01	—	Unverified
7	cso	SPL	0.01	—	Unverified
8	UCULab	SPL	0.01	—	Unverified
9	Habitat Team (RGBD+DD-PPO)	SPL	0	—	Unverified
10	RandomAgent	SPL	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VO	SPL	0.61	—	Unverified
2	OccupancyAnticipation	SPL	0.6	—	Unverified
3	DAN	SPL	0.53	—	Unverified
4	Visual Odometry for Realistic PointGoal Navigation	SPL	0.5	—	Unverified
5	ego-localization	SPL	0.31	—	Unverified
6	Information Bottleneck	SPL	0.13	—	Unverified
7	Alstar	SPL	0.05	—	Unverified
8	RandomAgent	SPL	0	—	Unverified
9	UCULab	SPL	0	—	Unverified