SOTAVerified

Motion Planning

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 426–450 of 920 papers

TitleStatusHype
kPAM-SC: Generalizable Manipulation Planning using KeyPoint Affordance and Shape Completion—0
Learning from Naturalistic Driving Data for Human-like Autonomous Highway Driving—0
λ: A Benchmark for Data-Efficiency in Long-Horizon Indoor Mobile Manipulation Robotics—0
Design, Control, and Motion-Planning for a Root-Perching Rotor-Distributed Manipulator—0
Design and Implementation of Hardware Accelerators for Neural Processing Applications—0
From Real World to Logic and Back: Learning Generalizable Relational Concepts For Long Horizon Robot Planning—0
Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles—0
From Motion to Muscle—0
Large Scale Distributed Collaborative Unlabeled Motion Planning with Graph Policy Gradients—0
Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset—0
Large Scale Interactive Motion Forecasting for Autonomous Driving: The Waymo Open Motion Dataset—0
Combining Graph Attention Networks and Distributed Optimization for Multi-Robot Mixed-Integer Convex Programming—0
Approximating Constraint Manifolds Using Generative Models for Sampling-Based Constrained Motion Planning—0
Layered Multirate Control of Constrained Linear Systems—0
From Motion to Behavior: Hierarchical Modeling of Humanoid Generative Behavior Control—0
Free-configuration Biased Sampling for Motion Planning: Errata—0
Learned Critical Probabilistic Roadmaps for Robotic Motion Planning—0
Combining Deep Reinforcement Learning with a Jerk-Bounded Trajectory Generator for Kinematically Constrained Motion Planning—0
Forming Real-World Human-Robot Cooperation for Tasks With General Goal—0
Combined Task and Motion Planning as Classical AI Planning—0
Learning and Inferring Movement with Deep Generative Model—0
Approximate Inference-based Motion Planning by Learning and Exploiting Low-Dimensional Latent Variable Models—0
Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding—0
Learning-Based Synthesis of Safety Controllers—0
Combinatorics of a Discrete Trajectory Space for Robot Motion Planning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified