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
Who Plays First? Optimizing the Order of Play in Stackelberg Games with Many Robots—0
Conservative and Risk-Aware Offline Multi-Agent Reinforcement LearningCode0
Timed-Elastic-Band Based Variable Splitting for Autonomous Trajectory Planning—0
A Robust Super-resolution Gridless Imaging Framework for UAV-borne SAR Tomography—0
Quadrotor Takeoff Trajectory Planning in a One-Dimensional Uncertain Wind-field Aided by Wind-Sensing Infrastructure—0
Combining Belief Function Theory and Stochastic Model Predictive Control for Multi-Modal Uncertainty in Autonomous Driving—0
Optimization-based motion primitive automata for autonomous driving—0
Traffic Learning and Proactive UAV Trajectory Planning for Data Uplink in Markovian IoT Models—0
Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation—0
3D Lane Detection from Front or Surround-View using Joint-Modeling & Matching—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