COP: Control & Observability-aware Planning - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2022

COP: Control & Observability-aware Planning

Pascal Brault
  • Function : Author
  • PersonId : 1118072
Quentin Delamare
  • Function : Author
Stephan Weiss


In this research, we aim to answer the question: How to combine Closed-Loop State and Input Sensitivity-based with Observability-aware trajectory planning? These possibly opposite optimization objectives can be used to improve trajectory control tracking and, at the same time, estimation performance. Our proposed novel Control & Observability-aware Planning (COP) framework is the first that uses these possibly opposing objectives in a Single-Objective Optimization Problem (SOOP) based on the Augmented Weighted Tchebycheff method to perform the balancing of them and generation of Bézier curve-based trajectories. Statistically relevant simulations for a 3D quadrotor unmanned aerial vehicle (UAV) case study produce results that support our claims and show the negative correlation between both objectives. We were able to reduce the positional mean integral error norm as well as the estimation uncertainty with the same trajectory to comparable levels of the trajectories optimized with individual objectives.
Fichier principal
Vignette du fichier
ICRA22_3213_FI.pdf (899.22 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03654316 , version 1 (28-04-2022)





Christoph Böhm, Pascal Brault, Quentin Delamare, Paolo Giordano, Stephan Weiss. COP: Control & Observability-aware Planning. ICRA 2022 - IEEE International Conference on Robotics and Automation, May 2022, Philadelphia, United States. pp.3364-3370, ⟨10.1109/ICRA46639.2022.9812373⟩. ⟨hal-03654316⟩
81 View
68 Download



Gmail Facebook X LinkedIn More