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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 241–250 of 324 papers

TitleStatusHype
Trajectory Planning Under Environmental Uncertainty With Finite-Sample Safety GuaranteesCode0
UAV Trajectory Planning in Wireless Sensor Networks for Energy Consumption Minimization by Deep Reinforcement Learning—0
Variable-Horizon Guidance for Autonomous Rendezvous and Docking to a Tumbling Target—0
Multistage Stochastic Model Predictive Control for Urban Automated Driving—0
Resilient UAV Swarm Communications with Graph Convolutional Neural NetworkCode0
Disconnectivity-Aware Energy-Efficient Cargo-UAV Trajectory Planning with Minimum Handoffs—0
OctoPath: An OcTree Based Self-Supervised Learning Approach to Local Trajectory Planning for Mobile Robots—0
Stability Constrained Mobile Manipulation Planning on Rough Terrain—0
Fast Spline Trajectory Planning: Minimum Snap and Beyond—0
VM-MODNet: Vehicle Motion aware Moving Object Detection for Autonomous Driving—0
Show:102550
← PrevPage 25 of 33Next →
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