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 271–280 of 324 papers

TitleStatusHype
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
Bridging the Gap between Optimal Trajectory Planning and Safety-Critical Control with Applications to Autonomous Vehicles—0
Monocular Instance Motion Segmentation for Autonomous Driving: KITTI InstanceMotSeg Dataset and Multi-task Baseline—0
Imitation Learning for Autonomous Trajectory Learning of Robot Arms in Space—0
Driving among Flatmobiles: Bird-Eye-View occupancy grids from a monocular camera for holistic trajectory planning—0
Imitative Planning using Conditional Normalizing Flow—0
Intelligent Trajectory Planning in UAV-mounted Wireless Networks: A Quantum-Inspired Reinforcement Learning Perspective—0
Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments—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