VIGOR-MPC: Vision-Guided Objective Regulation MPC
Overview
Source roundup from published reports. Claims below are attributed to their publishers, not independently verified. arXiv Robotics — research abstracts: VIGOR-MPC: Vision-Guided Objective Regulation MPC. This paper presents VIGOR-MPC, a modular student-teacher framework for vision-guided control in autonomous navigation. The system distills a long-horizon MPC into a computationally lightweight short-horizon MPC, using on…
Generated from attributed reports · Updated 1 hours ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
Environment: simulation
“ves only the noisy, occluded context produced by a perception module and learns, via a multi-level recurrent mapping, to infer cost parameters that aim to recover the teacher's behavior despite missing information. We evaluate VIGOR-MPC on vision-based autonomous racing in simulation and on hardware. Using only onboard perception of the track, VIGOR-MPC generalizes to tracks unseen during training and approaches the”
Exact source · revision 1Source owner not reported
Report timeline
Follow attributed reports and material updates.
- arXiv Robotics — research abstractsVIGOR-MPC: Vision-Guided Objective Regulation MPC
This paper presents VIGOR-MPC, a modular student-teacher framework for vision-guided control in autonomous navigation. The system distills a long-horizon MPC into a computationally lightweight short-horizon MPC, using online vision-based cost parameter estimation. Evaluated in simulation and on hardware, VIGOR-MPC generalizes to unseen tracks and achieves lap times close to the teacher model while reducing computation by over 90%.
Event coverage history
There is not enough continuous observation data to show a trend.
Timezone · UTC
Article dates follow your selected timezone. Briefing editions use Hong Kong time (UTC+8).