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 111–120 of 324 papers

TitleStatusHype
Distributed Cooperative Control and Optimization of Connected Automated Vehicles Platoon Against Cut-in Behaviors of Social Drivers—0
Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms—0
Capturing Object Detection Uncertainty in Multi-Layer Grid Maps—0
From Turbulence to Tranquility: AI-Driven Low-Altitude Network—0
FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving—0
Disconnectivity-Aware Energy-Efficient Cargo-UAV Trajectory Planning with Minimum Handoffs—0
CGD: Constraint-Guided Diffusion Policies for UAV Trajectory Planning—0
Generative emulation of chaotic dynamics with coherent prior—0
Automatic driving lane change safety prediction model based on LSTM—0
A message-passing algorithm for multi-agent trajectory planning—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