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 101–125 of 324 papers

TitleStatusHype
Distributed Multi-Objective Dynamic Offloading Scheduling for Air-Ground Cooperative MEC—0
Distributed Dynamic Platoons Control and Junction Crossing Optimization for Mixed Traffic Flows in Smart Cities- Part I. Fundamentals, Theoretical and Automatic Decision Framework—0
Evaluation of 3D CNN Semantic Mapping for Rover Navigation—0
Explanation for Trajectory Planning using Multi-modal Large Language Model for Autonomous Driving—0
Exploiting Prior Knowledge in Preferential Learning of Individualized Autonomous Vehicle Driving Styles—0
Fair Play in the Fast Lane: Integrating Sportsmanship into Autonomous Racing Systems—0
Automatic Parameter Tuning of Self-Driving Vehicles—0
Fast Monte Carlo Tree Diffusion: 100x Speedup via Parallel Sparse Planning—0
Fast Spline Trajectory Planning: Minimum Snap and Beyond—0
Fault diagnosis for linear heterodirectional hyperbolic ODE-PDE systems using backstepping-based trajectory planning—0
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
High precision indoor positioning by means of LiDAR—0
Diffusion Models for Robotic Manipulation: A Survey—0
Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments—0
Guaranteed Reachability on Riemannian Manifolds for Unknown Nonlinear Systems—0
Diffusion Meets Options: Hierarchical Generative Skill Composition for Temporally-Extended Tasks—0
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All datasetsnuScenesToolBench

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST-P3 (Lidar)Collision-3s1.27—Unverified
2UniADCollision-3s0.71—Unverified
3VAD-Base [jiang2023vad]Collision-3s0.24—Unverified
4AD-MLPCollision-3s0.24—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT4-TOPGUNWin rate86.54—Unverified
2Attention BucketWin rate71.5—Unverified
3GPT4- DFSDTWin rate70.4—Unverified