Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.
Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.
Autonomous drilling and excavation technologies are revolutionizing geotechnical applications, enhancing safety, precision, and efficiency in hazardous environments. This chapter discusses the components, systems, and algorithms involved in autonomous operations while highlighting real-world applications and challenges. Furthermore, it explores the integration of machine learning and connectivity in optimizing operations and addressing economic and regulatory concerns.
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
References
Chapter_22_Auton.pdfClass Notes
Memorization
What we have learnt
Final Test
Revision Tests
Term: Autonomous Drilling
Definition: A process where machines conduct boring operations with minimal or no human input, utilizing feedback control and advanced sensors.
Term: Sensor Fusion
Definition: Combining multiple sensor inputs to improve the accuracy of data used for decision-making in autonomous systems.
Term: Machine Learning
Definition: A branch of artificial intelligence that enables systems to learn from data and make predictions or decisions without being explicitly programmed.
Term: Teleoperation
Definition: Remote control of autonomous machines allowing human intervention when required, typically in complex environments.
Term: Geofencing
Definition: A safety protocol that restricts the operational range of machines to prevent them from trespassing into areas where human presence is not allowed.