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 301–310 of 324 papers

Title	Date	Tasks	Status
Prioritized Planning Algorithms for Trajectory Coordination of Multiple Mobile Robots	Sep 8, 2014	Trajectory Planning	CodeCode Available
Efficient Multi-Agent Trajectory Planning with Feasibility Guarantee using Relative Bernstein Polynomial	Sep 23, 2019	Collision AvoidanceCPU	CodeCode Available
A Priority Map for Vision-and-Language Navigation with Trajectory Plans and Feature-Location Cues	Jul 24, 2022	cross-modal alignmentTrajectory Planning	CodeCode Available
Safe and Non-Conservative Trajectory Planning for Autonomous Driving Handling Unanticipated Behaviors of Traffic Participants	Jun 19, 2024	Autonomous DrivingModel Predictive Control	CodeCode Available
MMP++: Motion Manifold Primitives with Parametric Curve Models	Oct 26, 2023	Trajectory Planning	CodeCode Available
GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Driving	May 27, 2025	Autonomous DrivingBench2Drive	CodeCode Available
Fortify the Shortest Stave in Attention: Enhancing Context Awareness of Large Language Models for Effective Tool Use	Dec 7, 2023	RAGTrajectory Planning	CodeCode Available
V2X-Assisted Distributed Computing and Control Framework for Connected and Automated Vehicles under Ramp Merging Scenario	Oct 30, 2024	Distributed ComputingModel Predictive Control	CodeCode Available
Trajectory Planning Under Environmental Uncertainty With Finite-Sample Safety Guarantees	Aug 13, 2021	Trajectory Planning	CodeCode Available
Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning	Feb 13, 2024	Multi-agent Reinforcement LearningQ-Learning	CodeCode Available

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All datasets nuScenes ToolBench

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ST-P3 (Lidar)	Collision-3s	1.27	—	Unverified
2	UniAD	Collision-3s	0.71	—	Unverified
3	AD-MLP	Collision-3s	0.24	—	Unverified
4	VAD-Base [jiang2023vad]	Collision-3s	0.24	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GPT4-TOPGUN	Win rate	86.54	—	Unverified
2	Attention Bucket	Win rate	71.5	—	Unverified
3	GPT4- DFSDT	Win rate	70.4	—	Unverified