Human-Aware Path Planning With Improved Virtual Doppler Method in Highly Dynamic Environments

Cai, Kuanqi; Chen, Weinan; Wang, Chaoqun; Song, Shuang; Meng, Max Q.-H.

doi:10.1109/tase.2022.3175039

“…Nevertheless, this method lacks consideration of dynamic groups. To address this limitation, Cai et al [34] improved upon work [32] by further researching the modeling of dynamic groups, leading to the construction of the CR&HS model, which considers collision risk and human space. Subsequently, the Risk-RRT [35] is adopted along with an improved virtual doppler method, ultimately ensuring that the robot reaches the target point without venturing into crowded areas.…”

Section: Model-based Navigation Methodsmentioning

confidence: 99%

Human-Robot Harmonious Coexistence: A Robot Navigation Framework Follows Social Norms in Dynamic Scenarios

LingliYu,

JiaweiLuo,

WeiweiZhu

et al. 2023

Preprint

0

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Designing a path planner that provides humans with a comfortable experience is a crucial step in enabling robots to seamlessly integrate into human environments. In this paper, we propose a comprehensive framework that equips robots with the ability to navigate in human environments by taking into account social norms and predicting human trajectories. Firstly, we propose a generalized social space modeling method based on Gaussian Mixture Model (GMM). This model is used to constrain the robot's adherence to social norms and incorporates factors such as human posture, velocity, and group distribution. Secondly, to achieve collision-free navigation, we introduce a trajectory prediction method using a four-parameter logistic curve. This method considers human historical trajectory information, velocity constraints, and incorporates confidence weights. Finally, we use piecewise high-order polynomials to optimize robot's local trajectory spatiotemporally. The collision avoidance constraints between the robot and humans are carefully designed to maximize human comfort and robot sociability. To validate the effectiveness of our approach, we compare it with existing methods, and the results demonstrate a significant improvement in human comfort.

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“…Nevertheless, this method lacks consideration of dynamic groups. To address this limitation, Cai et al [34] improved upon work [32] by further researching the modeling of dynamic groups, leading to the construction of the CR&HS model, which considers collision risk and human space. Subsequently, the Risk-RRT [35] is adopted along with an improved virtual doppler method, ultimately ensuring that the robot reaches the target point without venturing into crowded areas.…”

Section: Model-based Navigation Methodsmentioning

confidence: 99%

Human-Robot Harmonious Coexistence: A Robot Navigation Framework Follows Social Norms in Dynamic Scenarios

LingliYu,

JiaweiLuo,

WeiweiZhu

et al. 2023

Preprint

0

View full text Add to dashboard Cite

Designing a path planner that provides humans with a comfortable experience is a crucial step in enabling robots to seamlessly integrate into human environments. In this paper, we propose a comprehensive framework that equips robots with the ability to navigate in human environments by taking into account social norms and predicting human trajectories. Firstly, we propose a generalized social space modeling method based on Gaussian Mixture Model (GMM). This model is used to constrain the robot's adherence to social norms and incorporates factors such as human posture, velocity, and group distribution. Secondly, to achieve collision-free navigation, we introduce a trajectory prediction method using a four-parameter logistic curve. This method considers human historical trajectory information, velocity constraints, and incorporates confidence weights. Finally, we use piecewise high-order polynomials to optimize robot's local trajectory spatiotemporally. The collision avoidance constraints between the robot and humans are carefully designed to maximize human comfort and robot sociability. To validate the effectiveness of our approach, we compare it with existing methods, and the results demonstrate a significant improvement in human comfort.

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Human Comfort Factors in People Navigation: Literature Review, Taxonomy and Framework

Kalenberg,

Hofmann,

Martin

et al. 2024

Communications in Computer and Information Science

0

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Human-Aware Path Planning With Improved Virtual Doppler Method in Highly Dynamic Environments

Cited by 8 publications

References 46 publications

Human-Robot Harmonious Coexistence: A Robot Navigation Framework Follows Social Norms in Dynamic Scenarios

Human-Robot Harmonious Coexistence: A Robot Navigation Framework Follows Social Norms in Dynamic Scenarios

Human-Robot Harmonious Coexistence: A Robot Navigation Framework Follows Social Norms in Dynamic Scenarios

Human Comfort Factors in People Navigation: Literature Review, Taxonomy and Framework

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