Reactive Navigation of the Ackermann Steering Robot in Unknown Environments

Mobile robots are now widely used in numerous real-world applications that have complex navigation requirements, especially in environments used by humans. This requires highly accurate navigation that can be performed in realtime. In this paper, a method for generating a smooth motion of nonholonomic mobile robots is proposed. It enables robots to move optimally toward the desired goal and allows fast path replanning when encountering unknown or dynamic obstacles. The method generates smooth, collision-free trajectories based on clothoids, ensuring high computational efficiency and suitability for realtime path planning. By applying a smoothing algorithm, the proposed method improves the robot's efficiency in terms of travel time and trajectory length from start to goal, as demonstrated by a comparison with model predictive control.

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Publication Details

Published
2025-02-12
DOI
https://doi.org/10.1109/icara64554.2025.10977587
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.28
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article

Reactive Navigation of the Ackermann Steering Robot in Unknown Environments

Ana Šelek, Ivan Hrabar, SAŠA ŠTEKOVIĆ
1 citations
Robotic Path Planning Algorithms
1.28
article

Reactive Navigation of the Ackermann Steering Robot in Unknown Environments

Ana Šelek, Ivan Hrabar, SAŠA ŠTEKOVIĆ
article en
1 citations

Abstract

Mobile robots are now widely used in numerous real-world applications that have complex navigation requirements, especially in environments used by humans. This requires highly accurate navigation that can be performed in realtime. In this paper, a method for generating a smooth motion of nonholonomic mobile robots is proposed. It enables robots to move optimally toward the desired goal and allows fast path replanning when encountering unknown or dynamic obstacles. The method generates smooth, collision-free trajectories based on clothoids, ensuring high computational efficiency and suitability for realtime path planning. By applying a smoothing algorithm, the proposed method improves the robot's efficiency in terms of travel time and trajectory length from start to goal, as demonstrated by a comparison with model predictive control.

University of Zagreb (HR)
Openalex Percentile: Top 21%
Robotic Path Planning Algorithms
1.28
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