Abstract
In this study, a topology-guided unified nonlinear model predictive control (NMPC) approach is proposed for autonomous navigation of a class of Hybrid Terrestrial and Aerial Quadrotors (HyTAQs) in unknown environments. The approach can fully exploit the hybrid terrestrial-aerial locomotion of the vehicle and as such ensure a high navigation efficiency. A unified terrestrial-aerial NMPC is first formulated with a type of complementarity constraints involving the hybrid dynamics, together with the collision avoidance constraints for safety. Further, a topological roadmap with both terrestrial and aerial paths is leveraged to guide the kinodynamic path searching and thus the unified NMPC. Then, a complete and distinctive navigation framework is established and validated on our self-developed HyTAQ. Compared with the existing unified terrestrial-aerial planning methods, ours takes the vehicle dynamics into account for the first attempt and achieves a more reasonable decision of modes switching. Experimental results are presented to demonstrate the effectiveness and superiority of the proposed approach.
| Original language | English |
|---|---|
| Pages (from-to) | 4835-4840 |
| Number of pages | 6 |
| Journal | IEEE International Conference on Intelligent Robots and Systems |
| DOIs | |
| State | Published - 2022 |
| Externally published | Yes |
| Event | 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 - Kyoto, Japan Duration: 23 Oct 2022 → 27 Oct 2022 |
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