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<p>Humanoid robots are popular in last couple of years and often found operating in indoor environments such as smart homes, healthcare facilities, and service centers. These robots to operate effectively it is essential for them to accurately perceive and localize surrounding users and devices to enable effective interaction and navigation. One important technique that supports this capability is Direction-of-Arrival (DOA) estimation, which identifies the direction from which signals arrive by utilizing antenna array systems. However, reliable DOA estimation in indoor wireless environments remains a challenging task due to multipath propagation, noise, and the presence of multiple simultaneously active user devices. To address this issue, this manuscript aims to report estimation of DOA using a Uniform Circular Antenna Array (UCAA) integrated with a humanoid robot. The DOA estimation is dealt here as an optimization problem. A modified version of the Fire Hawk Optimizer (MFHO), is reported here by introducing time-varying control parameters into the position update mechanism, including attraction strength, attraction decay, adaptive step size, stochastic perturbation, and distance-based interaction factor. The effectiveness of the proposed optimizer is first validated on 24 benchmark functions, where the MFHO demonstrates improved optimization capability over the original FHO. The proposed MFHO algorithm is subsequently applied to DOA estimation for indoor wireless localization scenarios involving 10 and 20 user devices. Performance is evaluated in comparison with Fire Hawk Optimizer (FHO), Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Multiple Signal Classification (MUSIC), and Spatial Spectrum Fusion Estimation and Localization (SSFEAL). Simulation results demonstrate the effectiveness of the proposed MFHO for DOA estimation using a humanoid robot model equipped with a head-mounted Uniform Circular Array. The results highlight its potential for robust sound source localization in reverberant indoor environments.</p>

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Direction of arrival estimation on a humanoid robot using uniform circular array with Modified Fire Hawk Optimizer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月3日

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  • Vaibhav Kumar Kamal,
  • Geetha P,
  • Satyasai Jagannath Nanda

摘要

Humanoid robots are popular in last couple of years and often found operating in indoor environments such as smart homes, healthcare facilities, and service centers. These robots to operate effectively it is essential for them to accurately perceive and localize surrounding users and devices to enable effective interaction and navigation. One important technique that supports this capability is Direction-of-Arrival (DOA) estimation, which identifies the direction from which signals arrive by utilizing antenna array systems. However, reliable DOA estimation in indoor wireless environments remains a challenging task due to multipath propagation, noise, and the presence of multiple simultaneously active user devices. To address this issue, this manuscript aims to report estimation of DOA using a Uniform Circular Antenna Array (UCAA) integrated with a humanoid robot. The DOA estimation is dealt here as an optimization problem. A modified version of the Fire Hawk Optimizer (MFHO), is reported here by introducing time-varying control parameters into the position update mechanism, including attraction strength, attraction decay, adaptive step size, stochastic perturbation, and distance-based interaction factor. The effectiveness of the proposed optimizer is first validated on 24 benchmark functions, where the MFHO demonstrates improved optimization capability over the original FHO. The proposed MFHO algorithm is subsequently applied to DOA estimation for indoor wireless localization scenarios involving 10 and 20 user devices. Performance is evaluated in comparison with Fire Hawk Optimizer (FHO), Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Multiple Signal Classification (MUSIC), and Spatial Spectrum Fusion Estimation and Localization (SSFEAL). Simulation results demonstrate the effectiveness of the proposed MFHO for DOA estimation using a humanoid robot model equipped with a head-mounted Uniform Circular Array. The results highlight its potential for robust sound source localization in reverberant indoor environments.