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Accurate Estimation of 3D-Repetitive-Trajectories using Kalman Filter, Machine Learning and Curve-Fitting Method for High-speed Target Interception

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Artificial Intelligence for Robotics and Autonomous Systems Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1093))

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Abstract

Accurate estimation of trajectory is essential for the capture of any high-speed target. This chapter estimates and formulates an interception strategy for the trajectory of a target moving in a repetitive loop using a combination of estimation and learning techniques. An extended Kalman filter estimates the current location of the target using the visual information in the first loop of the trajectory to collect data points. Then, a combination of Recurrent Neural Network (RNN) with least-square curve-fitting is used to accurately estimate the future positions for the subsequent loops. We formulate an interception strategy for the interception of a high-speed target moving in a three-dimensional curve using noisy visual information from a camera. The proposed framework is validated in the ROS-Gazebo environment for interception of a target moving in a repetitive figure-of-eight trajectory. Astroid, Deltoid, Limacon, Squircle, and Lemniscates of Bernoulli are some of the high-order curves used for algorithm validation.

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Acknowledgements

We would like to acknowledge the Robert Bosch Center for Cyber Physical Systems, Indian Institute of Science, Bangalore, and Khalifa University, Abu Dhabi, for partial financial support.

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Authors and Affiliations

  1. Department of Aerospace Engineering, Indian Institute of Science, Guidance Control and Decision Systems Laboratory (GCDSL), Bangalore, 560012, India

    Aakriti Agrawal, Aashay Bhise, Rohitkumar Arasanipalai, Lima Agnel Tony, Shuvrangshu Jana & Debasish Ghose

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  1. Aakriti Agrawal
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  2. Aashay Bhise
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  3. Rohitkumar Arasanipalai
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  4. Lima Agnel Tony
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  5. Shuvrangshu Jana
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  6. Debasish Ghose
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Correspondence to Debasish Ghose .

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Editors and Affiliations

  1. College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Ahmad Taher Azar

  2. College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Anis Koubaa

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Agrawal, A., Bhise, A., Arasanipalai, R., Tony, L.A., Jana, S., Ghose, D. (2023). Accurate Estimation of 3D-Repetitive-Trajectories using Kalman Filter, Machine Learning and Curve-Fitting Method for High-speed Target Interception. In: Azar, A.T., Koubaa, A. (eds) Artificial Intelligence for Robotics and Autonomous Systems Applications. Studies in Computational Intelligence, vol 1093. Springer, Cham. https://doi.org/10.1007/978-3-031-28715-2_4

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