SOTAVerified

Motion Planning

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

Papers

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Showing 426–450 of 920 papers

TitleStatusHype
kPAM-SC: Generalizable Manipulation Planning using KeyPoint Affordance and Shape Completion—0
Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning—0
λ: A Benchmark for Data-Efficiency in Long-Horizon Indoor Mobile Manipulation Robotics—0
LEAGUE: Guided Skill Learning and Abstraction for Long-Horizon Manipulation—0
Guided Imitation of Task and Motion Planning—0
Continuous Trajectory Planning Based on Learning Optimization in High Dimensional Input Space for Serial Manipulators—0
Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles—0
A review of motion planning algorithms for intelligent robotics—0
Large Scale Distributed Collaborative Unlabeled Motion Planning with Graph Policy Gradients—0
A Survey of Knowledge Representation in Service Robotics—0
Large Scale Interactive Motion Forecasting for Autonomous Driving: The Waymo Open Motion Dataset—0
A GP-based Robust Motion Planning Framework for Agile Autonomous Robot Navigation and Recovery in Unknown Environments—0
Guaranteed approximations of arbitrarily quantified reachability problems—0
Layered Multirate Control of Constrained Linear Systems—0
GSON: A Group-based Social Navigation Framework with Large Multimodal Model—0
Continuous Motion Planning with Temporal Logic Specifications using Deep Neural Networks—0
Grounded Vision-Language Interpreter for Integrated Task and Motion Planning—0
Constrained Motion Planning Networks X—0
A Survey of Federated Learning for Connected and Automated Vehicles—0
Graph Neural Networks for Motion Planning—0
Learning and Inferring Movement with Deep Generative Model—0
Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference—0
Graph learning in robotics: a survey—0
Constant-time Motion Planning with Anytime Refinement for Manipulation—0
A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified