SOTAVerified

Motion Planning

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 851–875 of 920 papers

TitleStatusHype
Predictive and Semantic Layout Estimation for Robotic Applications in Manhattan Worlds—0
Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder—0
A Framework for Probabilistic Generic Traffic Scene Prediction—0
Accelerated Labeling of Discrete Abstractions for Autonomous Driving Subject to LTL Specifications—0
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics—0
Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills—0
Learning Navigation Behaviors End-to-End with AutoRL—0
Deeply Informed Neural Sampling for Robot Motion PlanningCode0
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional NetworksCode0
Safe Navigation with Human Instructions in Complex Scenes—0
Learning to guide task and motion planning using score-space representation—0
Potentially Guided Bidirectionalized RRT* for Fast Optimal Path Planning in Cluttered Environments—0
Baidu Apollo EM Motion PlannerCode0
Entropy Maximization for Markov Decision Processes Under Temporal Logic Constraints—0
A Survey of Knowledge Representation in Service Robotics—0
Motion Planning NetworksCode0
Simplifying Reward Design through Divide-and-Conquer—0
Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles—0
Admissible Abstractions for Near-optimal Task and Motion Planning—0
Deep Neural Networks for Swept Volume Prediction Between Configurations—0
Safe learning-based optimal motion planning for automated driving—0
A Data-Driven Approach for Autonomous Motion Planning and Control in Off-Road Driving Scenarios—0
KnowRob 2.0 — A 2nd Generation Knowledge Processing Framework for Cognition-enabled Robotic Agents—0
Learning and Inferring Movement with Deep Generative Model—0
Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified