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 11–20 of 324 papers

TitleStatusHype
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-TuningCode2
Generative Planning with 3D-vision Language Pre-training for End-to-End Autonomous DrivingCode2
GPD-1: Generative Pre-training for DrivingCode2
Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenesCode2
ORFD: A Dataset and Benchmark for Off-Road Freespace DetectionCode2
RoCo: Dialectic Multi-Robot Collaboration with Large Language ModelsCode2
Dynamic Neural Potential Field: Online Trajectory Optimization in Presence of Moving ObstaclesCode1
DPMPC-Planner: A real-time UAV trajectory planning framework for complex static environments with dynamic obstaclesCode1
Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph ConstructionCode1
CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous DrivingCode1
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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