SOTAVerified

Motion Planning

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–275 of 920 papers

TitleStatusHype
Inherent Diverse Redundant Safety Mechanisms for AI-based Software Elements in Automotive Applications—0
Driving Everywhere with Large Language Model Policy Adaptation—0
Real-World Robot Applications of Foundation Models: A Review—0
Safe Human-UAS Collaboration Abstraction—0
Risk-Aware MPC for Stochastic Systems with Runtime Temporal LogicsCode0
Scalable Multi-modal Model Predictive Control via Duality-based Interaction PredictionsCode1
A GP-based Robust Motion Planning Framework for Agile Autonomous Robot Navigation and Recovery in Unknown Environments—0
Distance and Collision Probability Estimation from Gaussian Surface Models—0
Design and Implementation of Hardware Accelerators for Neural Processing Applications—0
Current Effect-eliminated Optimal Target Assignment and Motion Planning for a Multi-UUV System—0
VLP: Vision Language Planning for Autonomous Driving—0
Disentangled Neural Relational Inference for Interpretable Motion Prediction—0
CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving—0
READ: Retrieval-Enhanced Asymmetric Diffusion for Motion PlanningCode1
Unified Task and Motion Planning using Object-centric Abstractions of Motion Constraints—0
InsActor: Instruction-driven Physics-based Characters—0
Visualizing High-Dimensional Configuration Spaces: A Comprehensive Analytical Approach—0
Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection—0
DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous DrivingCode1
Optimal Motion Planning using Finite Fourier Series in a Learning-based Collision Field—0
The Parameterized Complexity of Coordinated Motion Planning—0
Minimum-Time Trajectory Optimization With Data-Based Models: A Linear Programming Approach—0
Graph-based Prediction and Planning Policy Network (GP3Net) for scalable self-driving in dynamic environments using Deep Reinforcement Learning—0
Deep Reinforcement Learning Graphs: Feedback Motion Planning via Neural Lyapunov Verification—0
Automated Lane Merging via Game Theory and Branch Model Predictive ControlCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified