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 181–190 of 324 papers

TitleStatusHype
Active Learning for Nonlinear System Identification with Guarantees—0
Actuator Trajectory Planning for UAVs with Overhead Manipulator using Reinforcement Learning—0
Adaptive Field Effect Planner for Safe Interactive Autonomous Driving on Curved Roads—0
A Dynamic Motion Planning Framework for Autonomous Driving in Urban Environments—0
Aether: Geometric-Aware Unified World Modeling—0
A Fully-Integrated Sensing and Control System for High-Accuracy Mobile Robotic Building Construction—0
A Holistic Optimization Framework for Energy Efficient UAV-assisted Fog Computing: Attitude Control, Trajectory Planning and Task Assignment—0
A Learning-Based Trajectory Planning of Multiple UAVs for AoI Minimization in IoT Networks—0
Algorithms of Real-Time Navigation and Control of Autonomous Unmanned Vehicles—0
AlphaPilot: Autonomous Drone Racing—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