SOTAVerified

Trajectory Planning

Trajectory planning for industrial robots consists of moving the tool center point from point A to point B while avoiding body collisions over time. Trajectory planning is sometimes referred to as motion planning and erroneously as path planning. Trajectory planning is distinct from path planning in that it is parametrized by time. Essentially trajectory planning encompasses path planning in addition to planning how to move based on velocity, time, and kinematics.

Papers

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Showing 211–220 of 324 papers

TitleStatusHype
Stochastic Time-Optimal Trajectory Planning for Connected and Automated Vehicles in Mixed-Traffic Merging Scenarios—0
Submodular Trajectory Optimization for Aerial 3D Scanning—0
Surrogate Neural Networks for Efficient Simulation-based Trajectory Planning Optimization—0
Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles—0
Synergising Human-like Responses and Machine Intelligence for Planning in Disaster Response—0
Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM)—0
Taking a PEEK into YOLOv5 for Satellite Component Recognition via Entropy-based Visual Explanations—0
Task-Oriented Co-Design of Communication, Computing, and Control for Edge-Enabled Industrial Cyber-Physical Systems—0
The Fellowship of the Dyson Ring: ACT&Friends' Results and Methods for GTOC 11—0
Three-Dimension Collision-Free Trajectory Planning of UAVs Based on ADS-B Information in Low-Altitude Urban Airspace—0
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All datasetsnuScenesToolBench

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST-P3 (Lidar)Collision-3s1.27—Unverified
2UniADCollision-3s0.71—Unverified
3VAD-Base [jiang2023vad]Collision-3s0.24—Unverified
4AD-MLPCollision-3s0.24—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT4-TOPGUNWin rate86.54—Unverified
2Attention BucketWin rate71.5—Unverified
3GPT4- DFSDTWin rate70.4—Unverified