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 126–150 of 324 papers

TitleStatusHype
Hierarchical Task Offloading for UAV-Assisted Vehicular Edge Computing via Deep Reinforcement Learning—0
Attention-Enhanced Prompt Decision Transformers for UAV-Assisted Communications with AoI—0
Deep RL-based Trajectory Planning for AoI Minimization in UAV-assisted IoT—0
Deep Reinforcement Learning with a Stage Incentive Mechanism of Dense Reward for Robotic Trajectory Planning—0
Attention-based UAV Trajectory Optimization for Wireless Power Transfer-assisted IoT Systems—0
Altitude-Loss Optimal Glides in Engine Failure Emergencies -- Accounting for Ground Obstacles and Wind—0
Deep reinforcement learning for optical systems: A case study of mode-locked lasers—0
Learning-Aided Control of Robotic Tether-Net with Maneuverable Nodes to Capture Large Space Debris—0
Deep Reinforcement Learning for Motion Planning of Mobile Robots—0
A Successive-Elimination Approach to Adaptive Robotic Sensing—0
Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping—0
AlphaPilot: Autonomous Drone Racing—0
Adaptive Field Effect Planner for Safe Interactive Autonomous Driving on Curved Roads—0
Learning-Initialized Trajectory Planning in Unknown Environments—0
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles—0
Joint Cluster Head Selection and Trajectory Planning in UAV-Aided IoT Networks by Reinforcement Learning with Sequential Model—0
Data Driven Aircraft Trajectory Prediction with Deep Imitation Learning—0
Is That Rain? Understanding Effects on Visual Odometry Performance for Autonomous UAVs and Efficient DNN-based Rain Classification at the Edge—0
Assembly robots with optimized control stiffness through reinforcement learning—0
LaPlaSS: Latent Space Planning for Stochastic Systems—0
LBGP: Learning Based Goal Planning for Autonomous Following in Front—0
Algorithms of Real-Time Navigation and Control of Autonomous Unmanned Vehicles—0
Learning Maximal Safe Sets Using Hypernetworks for MPC-based Local Trajectory Planning in Unknown Environments—0
Learning Deep Sensorimotor Policies for Vision-based Autonomous Drone Racing—0
Accelerating the Evolution of Personalized Automated Lane Change through Lesson Learning—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