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 21–30 of 324 papers

TitleStatusHype
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
CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous DrivingCode1
Safe and Efficient Coexistence of Autonomous Vehicles with Human-Driven Traffic at Signalized Intersections—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