Feasible Space Monitoring for Multiple Control Barrier Functions with application to Large Scale Indoor Navigation
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2023
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866909410972925952 |
|---|---|
| author | Parwana, Hardik Black, Mitchell Hoxha, Bardh Okamoto, Hideki Fainekos, Georgios Prokhorov, Danil Panagou, Dimitra |
| author_facet | Parwana, Hardik Black, Mitchell Hoxha, Bardh Okamoto, Hideki Fainekos, Georgios Prokhorov, Danil Panagou, Dimitra |
| contents | Quadratic programs (QP) subject to multiple time-dependent control barrier function (CBF) based constraints have been used to design safety-critical controllers. However, ensuring the existence of a solution at all times to the QP subject to multiple CBF constraints (hereby called compatibility) is non-trivial. We quantify the feasible control input space defined by multiple CBFs at a state in terms of its volume. We then introduce a novel feasible space (FS) CBF that prevents this volume from going to zero. FS-CBF is shown to be a sufficient condition for the compatibility of multiple CBFs. For high-dimensional systems though, finding a valid FS-CBF may be difficult due to the limitations of existing computational hardware or theoretical approaches. In such cases, we show empirically that imposing the feasible space volume as a candidate FS-CBF not only enhances feasibility but also exhibits reduced sensitivity to changes in the user-chosen parameters such as gains of the nominal controller. Finally, paired with a global planner, we evaluate our controller for navigation among other dynamically moving agents in the AWS Hospital gazebo environment. The proposed controller is demonstrated to outperform the standard CBF-QP controller in maintaining feasibility. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_07803 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Feasible Space Monitoring for Multiple Control Barrier Functions with application to Large Scale Indoor Navigation Parwana, Hardik Black, Mitchell Hoxha, Bardh Okamoto, Hideki Fainekos, Georgios Prokhorov, Danil Panagou, Dimitra Robotics Optimization and Control Quadratic programs (QP) subject to multiple time-dependent control barrier function (CBF) based constraints have been used to design safety-critical controllers. However, ensuring the existence of a solution at all times to the QP subject to multiple CBF constraints (hereby called compatibility) is non-trivial. We quantify the feasible control input space defined by multiple CBFs at a state in terms of its volume. We then introduce a novel feasible space (FS) CBF that prevents this volume from going to zero. FS-CBF is shown to be a sufficient condition for the compatibility of multiple CBFs. For high-dimensional systems though, finding a valid FS-CBF may be difficult due to the limitations of existing computational hardware or theoretical approaches. In such cases, we show empirically that imposing the feasible space volume as a candidate FS-CBF not only enhances feasibility but also exhibits reduced sensitivity to changes in the user-chosen parameters such as gains of the nominal controller. Finally, paired with a global planner, we evaluate our controller for navigation among other dynamically moving agents in the AWS Hospital gazebo environment. The proposed controller is demonstrated to outperform the standard CBF-QP controller in maintaining feasibility. |
| title | Feasible Space Monitoring for Multiple Control Barrier Functions with application to Large Scale Indoor Navigation |
| topic | Robotics Optimization and Control |
| url | https://arxiv.org/abs/2312.07803 |