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 51–60 of 324 papers

TitleStatusHype
Mathematical Reasoning for Unmanned Aerial Vehicles: A RAG-Based Approach for Complex Arithmetic ReasoningCode0
From Turbulence to Tranquility: AI-Driven Low-Altitude Network—0
Using Diffusion Ensembles to Estimate Uncertainty for End-to-End Autonomous Driving—0
World Models for Cognitive Agents: Transforming Edge Intelligence in Future Networks—0
TrackVLA: Embodied Visual Tracking in the Wild—0
Articulatory modeling of the S-shaped F2 trajectories observed in Öhman's spectrographic analysis of VCV syllables—0
Attention-Enhanced Prompt Decision Transformers for UAV-Assisted Communications with AoI—0
GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous DrivingCode0
Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling—0
FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving—0
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All datasetsnuScenesToolBench

Benchmark Results

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