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

Showing 376400 of 542 papers

TitleStatusHype
Semantic Segmentation of Surface from Lidar Point Cloud0
Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents0
Future Frame Prediction of a Video Sequence0
LC-NAS: Latency Constrained Neural Architecture Search for Point Cloud Networks0
Occupancy Anticipation for Efficient Exploration and NavigationCode1
Spatial Geometric Reasoning for Room Layout Estimation via Deep Reinforcement Learning0
Inertial Safety from Structured Light0
Low Dimensional State Representation Learning with Reward-shaped Priors0
Online Visual Place Recognition via Saliency Re-identificationCode1
BiTraP: Bi-directional Pedestrian Trajectory Prediction with Multi-modal Goal EstimationCode1
Socially and Contextually Aware Human Motion and Pose Forecasting0
Situated Multimodal Control of a Mobile Robot: Navigation through a Virtual Environment0
Object Goal Navigation using Goal-Oriented Semantic ExplorationCode1
Learning Navigation Costs from Demonstration with Semantic Observations0
Learning Navigation Costs from Demonstrations with Semantic Observations0
Translating Natural Language Instructions for Behavioral Robot Navigation with a Multi-Head Attention Mechanism0
Distributed multi-robot collision avoidance via deep reinforcement learning for navigation in complex scenarios0
Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environmentsCode1
A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes0
Fast Geometric Surface based Segmentation of Point Cloud from Lidar Data0
Sim-to-Real Transfer with Incremental Environment Complexity for Reinforcement Learning of Depth-Based Robot Navigation0
How to reduce computation time while sparing performance during robot navigation? A neuro-inspired architecture for autonomous shifting between model-based and model-free learning0
Tradeoff-Focused Contrastive Explanation for MDP Planning0
On the Generalization Capability of Evolved Counter-propagation Neuro-controllers for Robot Navigation0
Using Generative Adversarial Nets on Atari Games for Feature Extraction in Deep Reinforcement Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SemExpSPL0.25Unverified
2SRCB-robot-sudoerSPL0.12Unverified
3Active Exploration (Pre-explore )SPL0.11Unverified
4Blue OxSPL0.11Unverified
5RLSPL0.06Unverified
6Habitat-WebSPL0.03Unverified
7Objects In Mirror Are Closer Than They AppearSPL0Unverified
8CasaSPL0Unverified
9PPO RGBDSPL0Unverified
10Black SheepSPL0Unverified
#ModelMetricClaimedVerifiedStatus
1THDASPL0.09Unverified
26-Act TetherSPL0.08Unverified
3SRCB-robot-sudoerSPL0.07Unverified
4SemExpSPL0.07Unverified
5Active Exploration (Pre-explore )SPL0.04Unverified
6RGBD+DD-PPOSPL0.02Unverified
7RL_20_torch_18SPL0.02Unverified
8Blue OxSPL0.02Unverified
9Black SheepSPL0Unverified
10RandomAgentSPL0Unverified
#ModelMetricClaimedVerifiedStatus
1VOSPL0.53Unverified
2SLAM-net + D*SPL0.38Unverified
3OccupancyAnticipationSPL0.22Unverified
4Information BottleneckSPL0.12Unverified
5ego-localizationSPL0.12Unverified
639SPL0.01Unverified
7csoSPL0.01Unverified
8UCULabSPL0.01Unverified
9Habitat Team (RGBD+DD-PPO)SPL0Unverified
10RandomAgentSPL0Unverified
#ModelMetricClaimedVerifiedStatus
1VOSPL0.61Unverified
2OccupancyAnticipationSPL0.6Unverified
3DANSPL0.53Unverified
4Visual Odometry for Realistic PointGoal NavigationSPL0.5Unverified
5ego-localizationSPL0.31Unverified
6Information BottleneckSPL0.13Unverified
7AlstarSPL0.05Unverified
8RandomAgentSPL0Unverified
9UCULabSPL0Unverified