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

Showing 5160 of 324 papers

TitleStatusHype
Perception-and-Energy-aware Motion Planning for UAV using Learning-based Model under Heteroscedastic UncertaintyCode0
Parallelization of Monte Carlo Tree Search in Continuous DomainsCode0
Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language ModelsCode0
Prioritized Planning Algorithms for Trajectory Coordination of Multiple Mobile RobotsCode0
Non-iterative Optimization of Trajectory and Radio Resource for Aerial NetworkCode0
Learning Reward Models for Cooperative Trajectory Planning with Inverse Reinforcement Learning and Monte Carlo Tree SearchCode0
MMP++: Motion Manifold Primitives with Parametric Curve ModelsCode0
GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous DrivingCode0
Machine Learning Optimized Orthogonal Basis Piecewise Polynomial ApproximationCode0
Formation Control for Connected and Automated Vehicles on Multi-lane Roads: Relative Motion Planning and Conflict ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST-P3 (Lidar)Collision-3s1.27Unverified
2UniADCollision-3s0.71Unverified
3AD-MLPCollision-3s0.24Unverified
4VAD-Base [jiang2023vad]Collision-3s0.24Unverified
#ModelMetricClaimedVerifiedStatus
1GPT4-TOPGUNWin rate86.54Unverified
2Attention BucketWin rate71.5Unverified
3GPT4- DFSDTWin rate70.4Unverified