DART-S: Reachability-Audited Active-Suspension Preconditioning for Off-Road Vehicle Jumps

DART-S: Reachability-Audited Active-Suspension Preconditioning for Off-Road Vehicle Jumps

|Authors: Yu Hu, Fangzhou Zhao, Liang Chen, Chen Min, Wei Li, Mingyuan Sang, Jiajia Ma, Shican Chen, Di Pang, Baolei Chen

|Venue: arXiv preprint | Year: 2026

|arXiv: 2608.20275v1

Abstract

Airborne torque reaction cannot recover takeoff errors beyond the wheel angular-momentum budget. DART-S applies ramp-face suspension preconditioning to change pitch, pitch rate, and wheel spin before liftoff, thereby shifting the queried state and altering the remaining authority budget. To predict how each suspension action reshapes this state-budget pair, DART-S employs a local calibration map. A support-aware selector combines the predicted shift with local outcome evidence and an interval-reachability screen; an exact-pair audit reports residual authority. Across 600 new runs in 72 independent BeamNG sessions, every positive, negative, and boundary query follows its prespecified branch. At the confirmed 40°/13 m/s boundary, DART-S attains 24/24 post-touchdown attitude-criterion successes versus 0/24 for DART (session-level Holm-adjusted p=0.0234). At 11.5 m/s, a 0.35 s timing action attains 23/24 versus 0/24 for the static preset (p=0.0156). The 200 rad/s command guard keeps drivetrain hard-limit exceedance at zero across all 600 runs. The source code will be available at https://github.com/MeridianCAS/DART-S

Key Contributions

• Airborne torque reaction cannot recover takeoff errors beyond the wheel angular-momentum budget
• DART-S applies ramp-face suspension preconditioning to change pitch, pitch rate, and wheel spin b…
• To predict how each suspension action reshapes this state-budget pair, DART-S employs a local cal…
• A support-aware selector combines the predicted shift with local outcome evidence and an interval…
• Across 600 new runs in 72 independent BeamNG sessions, every positive, negative, and boundary que…

Topics

• reinforcement-learning
• tactile

Code & Data

• GitHub repository: https://github.com/MeridianCAS/DART-S

BibTeX

@article{Hu2026_260820275v1,
  title     = {DART-S: Reachability-Audited Active-Suspension Preconditioning for Off-Road Vehicle Jumps},
  author    = {Yu Hu and Fangzhou Zhao and Liang Chen and Chen Min and Wei Li and Mingyuan Sang and Jiajia Ma and Shican Chen and Di Pang and Baolei Chen},
  year      = {2026},
  eprint    = {2608.20275v1},
  archivePrefix = {arXiv},
  primaryClass  = {cs.RO},
  url       = {https://arxiv.org/abs/2608.20275v1}
}