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 61–70 of 324 papers

TitleStatusHype
VERDI: VLM-Embedded Reasoning for Autonomous Driving—0
Provably safe and human-like car-following behaviors: Part 2. A parsimonious multi-phase model with projected braking—0
Provably safe and human-like car-following behaviors: Part 1. Analysis of phases and dynamics in standard models—0
TransDiffuser: End-to-end Trajectory Generation with Decorrelated Multi-modal Representation for Autonomous Driving—0
Optimal Trajectory Planning with Collision Avoidance for Autonomous Vehicle Maneuvering—0
Trajectory Planning with Model Predictive Control for Obstacle Avoidance Considering Prediction Uncertainty—0
Mixed Bernstein-Fourier Approximants for Optimal Trajectory Generation with Periodic Behavior—0
Adaptive Field Effect Planner for Safe Interactive Autonomous Driving on Curved Roads—0
Generative emulation of chaotic dynamics with coherent prior—0
Diffusion Models for Robotic Manipulation: A Survey—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