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 191–200 of 324 papers

TitleStatusHype
Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing—0
Bayesian Optimization Enhanced Deep Reinforcement Learning for Trajectory Planning and Network Formation in Multi-UAV Networks—0
Standoff Tracking Using DNN-Based MPC with Implementation on FPGA—0
Planning-oriented Autonomous DrivingCode4
Towards Accurate Ground Plane Normal Estimation from Ego-MotionCode1
Benchmark for Models Predicting Human Behavior in Gap Acceptance Scenarios—0
Learning Deep Sensorimotor Policies for Vision-based Autonomous Drone Racing—0
Backflipping with Miniature Quadcopters by Gaussian Process Based Control and Planning—0
SAFER: Safe Collision Avoidance using Focused and Efficient Trajectory Search with Reinforcement Learning—0
Computing Forward Reachable Sets for Nonlinear Adaptive Multirotor Controllers—0
Show:102550
← PrevPage 20 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