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Motion Planning

( Image credit: Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 776–800 of 920 papers

TitleStatusHype
Robot Motion Planning as Video Prediction: A Spatio-Temporal Neural Network-based Motion Planner—0
Robot Navigation Anticipative Strategies in Deep Reinforcement Motion Planning—0
Robust Finite-State Controllers for Uncertain POMDPs—0
Robust Lattice-based Motion Planning—0
R-Pred: Two-Stage Motion Prediction Via Tube-Query Attention-Based Trajectory Refinement—0
RRT* Based Optimal Trajectory Generation with Linear Temporal Logic Specifications under Kinodynamic Constraints—0
RSRD: A Road Surface Reconstruction Dataset and Benchmark for Safe and Comfortable Autonomous Driving—0
RTGNN: A Novel Approach to Model Stochastic Traffic Dynamics—0
S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Modelwith Spatio-Temporal Visual Representation—0
S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Model with Spatio-Temporal Visual Representation—0
S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles—0
Safe Human-UAS Collaboration Abstraction—0
Safe, Learning-Based MPC for Highway Driving under Lane-Change Uncertainty: A Distributionally Robust Approach—0
Safe learning-based optimal motion planning for automated driving—0
Safely: Safe Stochastic Motion Planning Under Constrained Sensing via Duality—0
Safe Motion Planning against Multimodal Distributions based on a Scenario Approach—0
Safe Motion Planning in Unknown Environments: Optimality Benchmarks and Tractable Policies—0
Safe motion planning with environment uncertainty—0
Safe multi-agent motion planning under uncertainty for drones using filtered reinforcement learning—0
Safe Navigation with Human Instructions in Complex Scenes—0
Safe Output Feedback Motion Planning from Images via Learned Perception Modules and Contraction Theory—0
Safety-Aware Optimal Control for Motion Planning with Low Computing Complexity—0
Safety-Critical Traffic Simulation with Adversarial Transfer of Driving Intentions—0
Safety in Augmented Importance Sampling: Performance Bounds for Robust MPPI—0
SAMPLE-HD: Simultaneous Action and Motion Planning Learning Environment—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified