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 161–170 of 324 papers

TitleStatusHype
Optimizing Drug Delivery in Smart Pharmacies: A Novel Framework of Multi-Stage Grasping Network Combined with Adaptive Robotics Mechanism—0
Optimizing Energy-Efficient Braking Trajectories with Anticipatory Road Data for Automated Vehicles—0
Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey—0
Performance Analysis of Optimally Coordinated Connected and Automated Vehicles in a Mixed Traffic Environment—0
Performance Evaluation and Hybrid Application of the Greedy and Predictive UAV Trajectory Optimization Methods for Localizing a Target Mobile Device—0
Pioneering SE(2)-Equivariant Trajectory Planning for Automated Driving—0
Planning Brachistochrone Hip Trajectory for a Toe-Foot Bipedal Robot going Downstairs—0
Planning on the fast lane: Learning to interact using attention mechanisms in path integral inverse reinforcement learning—0
Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling—0
PLOP: Probabilistic poLynomial Objects trajectory Planning 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