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 276–300 of 324 papers

TitleStatusHype
Imitative Planning using Conditional Normalizing Flow—0
Intelligent Trajectory Planning in UAV-mounted Wireless Networks: A Quantum-Inspired Reinforcement Learning Perspective—0
Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments—0
Planning on the fast lane: Learning to interact using attention mechanisms in path integral inverse reinforcement learning—0
UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning ApproachCode1
Active Learning for Nonlinear System Identification with Guarantees—0
Evaluation of 3D CNN Semantic Mapping for Rover Navigation—0
Deep reinforcement learning for optical systems: A case study of mode-locked lasers—0
AlphaPilot: Autonomous Drone Racing—0
Data Driven Aircraft Trajectory Prediction with Deep Imitation Learning—0
High precision indoor positioning by means of LiDAR—0
Autonomous Emergency Collision Avoidance and Stabilisation in Structured Environments—0
Trajectory Planning and Control for Automatic Docking of ASVs with Full-Scale Experiments—0
Parallelization of Monte Carlo Tree Search in Continuous DomainsCode0
PLOP: Probabilistic poLynomial Objects trajectory Planning for autonomous driving—0
Mixed Strategies for Robust Optimization of Unknown Objectives—0
Assembly robots with optimized control stiffness through reinforcement learning—0
Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms—0
Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles—0
FASTER: Fast and Safe Trajectory Planner for Navigation in Unknown EnvironmentsCode2
Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey—0
Deep Reinforcement Learning for Motion Planning of Mobile Robots—0
A Dynamic Motion Planning Framework for Autonomous Driving in Urban Environments—0
Deep RL-based Trajectory Planning for AoI Minimization in UAV-assisted IoT—0
A Fully-Integrated Sensing and Control System for High-Accuracy Mobile Robotic Building Construction—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