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 261–270 of 324 papers

TitleStatusHype
LBGP: Learning Based Goal Planning for Autonomous Following in Front—0
Fault diagnosis for linear heterodirectional hyperbolic ODE-PDE systems using backstepping-based trajectory planning—0
A nonlinear tracking model predictive control scheme for dynamic target signals—0
Deep Reinforcement Learning with a Stage Incentive Mechanism of Dense Reward for Robotic Trajectory Planning—0
Artificial Intelligence Control in 4D Cylindrical Space for Industrial Robotic ApplicationsCode0
Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing—0
Stochastic Model Predictive Control with a Safety Guarantee for Automated Driving: Extended Version—0
Trajectory planning with a dynamic obstacle clustering strategy using Mixed-Integer Linear Programming—0
Energy-Efficient Multi-UAV Data Collection for IoT Networks with Time Deadlines—0
Semantic Segmentation of Surface from Lidar Point Cloud—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