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 21–30 of 324 papers

TitleStatusHype
Reinforced Imitative Trajectory Planning for Urban Automated DrivingCode1
Dynamic Neural Potential Field: Online Trajectory Optimization in Presence of Moving ObstaclesCode1
BiC-MPPI: Goal-Pursuing, Sampling-Based Bidirectional Rollout Clustering Path Integral for Trajectory OptimizationCode1
Learning Discrete World Models for Heuristic SearchCode1
GNN-Empowered Effective Partial Observation MARL Method for AoI Management in Multi-UAV NetworkCode1
Probing Multimodal LLMs as World Models for DrivingCode1
LTLDoG: Satisfying Temporally-Extended Symbolic Constraints for Safe Diffusion-based PlanningCode1
WROOM: An Autonomous Driving Approach for Off-Road NavigationCode1
SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task ExecutionCode1
Time-Optimal Control for High-Order Chain-of-Integrators Systems with Full State Constraints and Arbitrary Terminal States (Extended Version)Code1
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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