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Motion Planning

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

Papers

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Showing 326–350 of 920 papers

TitleStatusHype
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models—0
An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems—0
Spatial Intelligence of a Self-driving Car and Rule-Based Decision Making—0
Using Implicit Behavior Cloning and Dynamic Movement Primitive to Facilitate Reinforcement Learning for Robot Motion Planning—0
Traffic Flow Simulation for Autonomous Driving—0
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review—0
A Multi-Heuristic Search-based Motion Planning for Automated Parking—0
CaRT: Certified Safety and Robust Tracking in Learning-based Motion Planning for Multi-Agent Systems—0
Robotic surface exploration with vision and tactile sensing for cracks detection and characterisation—0
Embodied Lifelong Learning for Task and Motion Planning—0
RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot—0
Collision-free Motion Planning for Mobile Robots by Zero-order Robust Optimization-based MPC—0
Adversarial Backdoor Attack by Naturalistic Data Poisoning on Trajectory Prediction in Autonomous Driving—0
SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Replicable ScenesCode1
Deep Transfer Learning for Intelligent Vehicle Perception: a Survey—0
DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability—0
Robot Learning with Sensorimotor Pre-training—0
Parting with Misconceptions about Learning-based Vehicle Motion PlanningCode2
Reinforcement Learning in Robotic Motion Planning by Combined Experience-based Planning and Self-Imitation Learning—0
AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and CheckersCode1
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement LearningCode1
Trajectory Prediction with Observations of Variable-Length for Motion Planning in Highway Merging scenariosCode1
Vehicle Dynamics Modeling for Autonomous Racing Using Gaussian Processes—0
Risk-Aware Reward Shaping of Reinforcement Learning Agents for Autonomous DrivingCode0
Scene as OccupancyCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified