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Communication Dans Un Congrès Année : 2022

Uncertainty-aware Navigation in Crowded Environment

Résumé

Robots are now widely used around humans, in homes and public places like the museums, all due to their many benefits. These autonomous robots are called social or service robots and they always find it difficult to navigate in crowded environments; largely because of the high level of uncertainty in observing and predicting human behaviours in a highly dynamic environment. Uncertainty is propagated during prediction and might grow to levels that renders the whole environment unsafe for the robot leading to the socalled Freezing Robot Problem – FRP. This work presents our proposed approach to proactively account for various uncertainties during the robot’s motion planning using a stochastic Nonlinear Model Predictive Controller (SNMPC). Additionally, using numerical optimization methods enables the planner to compute new control commands in realtime.
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Dates et versions

hal-03935338 , version 1 (11-01-2023)

Identifiants

Citer

Emmanuel Alao, Philippe Martinet. Uncertainty-aware Navigation in Crowded Environment. ICARCV 2022 - 17th International Conference on Control, Automation, Robotics and Vision, Dec 2022, Singapore, Singapore. pp.293-298, ⟨10.1109/ICARCV57592.2022.10004241⟩. ⟨hal-03935338⟩
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