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 461–470 of 542 papers

Title	Date	Tasks	Status
Deep Learning-Based Multi-Modal Fusion for Robust Robot Perception and Navigation	Apr 26, 2025	Autonomous NavigationRobot Navigation	—Unverified
Deep Local Trajectory Replanning and Control for Robot Navigation	May 13, 2019	Robot Navigation	—Unverified
DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance	Oct 4, 2019	Collision AvoidanceDeep Reinforcement Learning	—Unverified
Deep Reinforcement Learning to Acquire Navigation Skills for Wheel-Legged Robots in Complex Environments	Apr 27, 2018	Deep Reinforcement LearningNavigate	—Unverified
Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments	Dec 16, 2016	Deep Reinforcement Learningreinforcement-learning	—Unverified
Deep Sensor Fusion for Real-Time Odometry Estimation	Jul 31, 2019	Ordinal ClassificationRobot Navigation	—Unverified
DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport	Aug 14, 2023	Motion PlanningRobot Navigation	—Unverified
Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs	Aug 19, 2024	continuous-controlContinuous Control	—Unverified
DEUX: Active Exploration for Learning Unsupervised Depth Perception	Sep 16, 2023	Depth CompletionDepth Estimation	—Unverified
Differentiable Constrained Imitation Learning for Robot Motion Planning and Control	Oct 21, 2022	Decision MakingImitation Learning	—Unverified

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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