AN METHOD TO STOP DIFFERENTIAL MODELS OF FALLING OVER

AN METHOD TO STOP DIFFERENTIAL MODELS OF FALLING OVER

Sant'Anna, Tiago Barretto; Lima, Rebeca Tourinho

Full article:

Robotics is a rapidly growing field with a profound impact on various industries, aiming to design machines that assist humans in practical tasks. Autonomous navigation, a critical aspect of robotics, enables robots to move and operate independently without human intervention. However, navigating different environments presents numerous challenges, including the risk of robots tipping over, leading to damage or potential harm to humans. This article proposes a solution to prevent tipping in differential robots during autonomous navigation. The solution employs behavior trees, a computationally efficient approach, integrated into the robot's navigation system. By continuously monitoring data from an IMU sensor, the plugin effectively detects oscillatory movements and takes corrective actions, ensuring stable and safe robot operation.

Robotics is a rapidly growing field with a profound impact on various industries, aiming to design machines that assist humans in practical tasks. Autonomous navigation, a critical aspect of robotics, enables robots to move and operate independently without human intervention. However, navigating different environments presents numerous challenges, including the risk of robots tipping over, leading to damage or potential harm to humans. This article proposes a solution to prevent tipping in differential robots during autonomous navigation. The solution employs behavior trees, a computationally efficient approach, integrated into the robot's navigation system. By continuously monitoring data from an IMU sensor, the plugin effectively detects oscillatory movements and takes corrective actions, ensuring stable and safe robot operation.

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DOI: 10.5151/siintec2023-306179

Referências bibliográficas

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Como citar:

Sant'Anna, Tiago Barretto ; Lima, Rebeca Tourinho ; "AN METHOD TO STOP DIFFERENTIAL MODELS OF FALLING OVER", p-392-399. In: . São Paulo: Blucher, 2023.
ISSN 23577592, DOI 10.5151/siintec2023-306179