SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–450 of 542 papers

TitleStatusHype
Semantic Segmentation of Surface from Lidar Point Cloud—0
Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents—0
Future Frame Prediction of a Video Sequence—0
LC-NAS: Latency Constrained Neural Architecture Search for Point Cloud Networks—0
Inertial Safety from Structured Light—0
Spatial Geometric Reasoning for Room Layout Estimation via Deep Reinforcement Learning—0
Low Dimensional State Representation Learning with Reward-shaped Priors—0
Socially and Contextually Aware Human Motion and Pose Forecasting—0
Situated Multimodal Control of a Mobile Robot: Navigation through a Virtual Environment—0
Learning Navigation Costs from Demonstration with Semantic Observations—0
Learning Navigation Costs from Demonstrations with Semantic Observations—0
Translating Natural Language Instructions for Behavioral Robot Navigation with a Multi-Head Attention Mechanism—0
Distributed multi-robot collision avoidance via deep reinforcement learning for navigation in complex scenarios—0
A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes—0
Fast Geometric Surface based Segmentation of Point Cloud from Lidar Data—0
Sim-to-Real Transfer with Incremental Environment Complexity for Reinforcement Learning of Depth-Based Robot Navigation—0
How to reduce computation time while sparing performance during robot navigation? A neuro-inspired architecture for autonomous shifting between model-based and model-free learning—0
Tradeoff-Focused Contrastive Explanation for MDP Planning—0
On the Generalization Capability of Evolved Counter-propagation Neuro-controllers for Robot Navigation—0
Using Generative Adversarial Nets on Atari Games for Feature Extraction in Deep Reinforcement Learning—0
APPLD: Adaptive Planner Parameter Learning from Demonstration—0
Optimized Directed Roadmap Graph for Multi-Agent Path Finding Using Stochastic Gradient Descent—0
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey—0
Adversarial Attacks on Monocular Depth Estimation—0
Multiplicative Controller Fusion: Leveraging Algorithmic Priors for Sample-efficient Reinforcement Learning and Safe Sim-To-Real TransferCode0
Deep Active Inference for Autonomous Robot Navigation—0
Robust Policy Search for Robot Navigation—0
Training Adversarial Agents to Exploit Weaknesses in Deep Control PoliciesCode0
Learning Navigation Costs from Demonstration in Partially Observable Environments—0
On Reward Shaping for Mobile Robot Navigation: A Reinforcement Learning and SLAM Based Approach—0
Robot Navigation in Unseen Spaces using an Abstract Map—0
Stochastic Finite State Control of POMDPs with LTL Specifications—0
Assurance Monitoring of Cyber-Physical Systems with Machine Learning Components—0
High-Level Plan for Behavioral Robot Navigation with Natural Language Directions and R-NET—0
ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization—0
NeuRoRA: Neural Robust Rotation AveragingCode0
Effects of a Social Force Model reward in Robot Navigation based on Deep Reinforcement Learning—0
Kernel learning for visual perceptionCode0
Three Dimensional Route Planning for Multiple Unmanned Aerial Vehicles using Salp Swarm Algorithm—0
Planning with Goal-Conditioned PoliciesCode0
Robot navigation and target capturing using nature-inspired approaches in a dynamic environment—0
Towards Automatic Annotation for Semantic Segmentation in Drone Videos—0
Learning Continuous Occupancy Maps with the Ising Process Model—0
Topological Navigation Graph Framework—0
A Hybrid Compact Neural Architecture for Visual Place RecognitionCode0
Measuring robustness of Visual SLAM—0
Object Segmentation Tracking from Generic Video Cues—0
DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance—0
Spatial Correspondence With Generative Adversarial Network: Learning Depth From Monocular Videos—0
Interaction-Aware Multi-Agent Reinforcement Learning for Mobile Agents with Individual Goals—0
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All datasetsHabitat 2020 Object Nav minivalHabitat 2020 Object Nav test-stdHabitat 2020 Point Nav test-stdHabitat 2020 Point Nav minival

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SemExpSPL0.25—Unverified
2SRCB-robot-sudoerSPL0.12—Unverified
3Active Exploration (Pre-explore )SPL0.11—Unverified
4Blue OxSPL0.11—Unverified
5RLSPL0.06—Unverified
6Habitat-WebSPL0.03—Unverified
7Objects In Mirror Are Closer Than They AppearSPL0—Unverified
8CasaSPL0—Unverified
9PPO RGBDSPL0—Unverified
10Black SheepSPL0—Unverified
#ModelMetricClaimedVerifiedStatus
1THDASPL0.09—Unverified
26-Act TetherSPL0.08—Unverified
3SRCB-robot-sudoerSPL0.07—Unverified
4SemExpSPL0.07—Unverified
5Active Exploration (Pre-explore )SPL0.04—Unverified
6RGBD+DD-PPOSPL0.02—Unverified
7RL_20_torch_18SPL0.02—Unverified
8Blue OxSPL0.02—Unverified
9Black SheepSPL0—Unverified
10RandomAgentSPL0—Unverified
#ModelMetricClaimedVerifiedStatus
1VOSPL0.53—Unverified
2SLAM-net + D*SPL0.38—Unverified
3OccupancyAnticipationSPL0.22—Unverified
4Information BottleneckSPL0.12—Unverified
5ego-localizationSPL0.12—Unverified
639SPL0.01—Unverified
7csoSPL0.01—Unverified
8UCULabSPL0.01—Unverified
9Habitat Team (RGBD+DD-PPO)SPL0—Unverified
10RandomAgentSPL0—Unverified
#ModelMetricClaimedVerifiedStatus
1VOSPL0.61—Unverified
2OccupancyAnticipationSPL0.6—Unverified
3DANSPL0.53—Unverified
4Visual Odometry for Realistic PointGoal NavigationSPL0.5—Unverified
5ego-localizationSPL0.31—Unverified
6Information BottleneckSPL0.13—Unverified
7AlstarSPL0.05—Unverified
8RandomAgentSPL0—Unverified
9UCULabSPL0—Unverified