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 311–320 of 324 papers

TitleStatusHype
Cooperative Trajectory Planning in Uncertain Environments with Monte Carlo Tree Search and Risk Metrics—0
Cooperative Trajectory Planning: Principles for Human-Machine System Design on Trajectory Level—0
Data Driven Aircraft Trajectory Prediction with Deep Imitation Learning—0
Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping—0
Deep Reinforcement Learning for Motion Planning of Mobile Robots—0
Deep reinforcement learning for optical systems: A case study of mode-locked lasers—0
Deep Reinforcement Learning with a Stage Incentive Mechanism of Dense Reward for Robotic Trajectory Planning—0
Deep RL-based Trajectory Planning for AoI Minimization in UAV-assisted IoT—0
Diffusion Meets Options: Hierarchical Generative Skill Composition for Temporally-Extended Tasks—0
Diffusion Models for Robotic Manipulation: A Survey—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