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 101–110 of 324 papers

TitleStatusHype
A nonlinear real time capable motion cueing algorithm based on deep reinforcement learning—0
Aether: Geometric-Aware Unified World Modeling—0
Evaluation of 3D CNN Semantic Mapping for Rover Navigation—0
Explanation for Trajectory Planning using Multi-modal Large Language Model for Autonomous Driving—0
Exploiting Prior Knowledge in Preferential Learning of Individualized Autonomous Vehicle Driving Styles—0
Fair Play in the Fast Lane: Integrating Sportsmanship into Autonomous Racing Systems—0
Action and Trajectory Planning for Urban Autonomous Driving with Hierarchical Reinforcement Learning—0
3D UAV Trajectory Planning for IoT Data Collection via Matrix-Based Evolutionary Computation—0
Fast Spline Trajectory Planning: Minimum Snap and Beyond—0
Calculation of time-optimal motion primitives for systems exhibiting oscillatory internal dynamics—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