Abstract
Frequent fluctuations in the environment's temperature and climate significantly impact our crop fields. Floods and droughts occur in different places in different seasons, which is very unusual and affects the crops' health and productivity. During these calamities, they are also not able to monitor their crop fields. However, if it is possible by providing farmers with information about their fields' conditions like temperature, pressure, and soil moisture, we can help them assess environmental conditions for specific areas. This data can also aid farmers in determining the appropriate amounts of fertilizers and pesticides to apply to their crops and which crops are best suited for their fields. Developing data-driven models for such applications can effectively address this issue, enabling predictions for optimal crop choices based on field quality and seasonal conditions. However, conducting large-scale data collection in agricultural fields through traditional methods is time-consuming and resource-intensive. Furthermore, geologists and earth scientists can also benefit from this data for their research purposes. To address these challenges, we have designed and fabricated a bio-inspired modular robot capable of hopping and flying within the target area to collect real-time data with spatial and temporal variations. The primary goal of this robot is to achieve agile and versatile movement suitable for a variety of surveillance applications. Drawing inspiration from nature's remarkable jumping abilities, the robot's design incorporates principles of efficient energy transfer and dynamic control. Utilizing a unique thrust mechanism characterized by a rich trajectory and metamorphic features, the robot demonstrates remarkable hopping efficiency, propelled by only two servo motors as actuators. To enhance its capabilities, the robot integrates three legs to facilitate self-righting, steering, and take-off. The presence of three legs aids in stabilizing the robot during falls, contributing to its overall robustness. Additionally, the robot's ability to adjust its center of mass (COM) using the main body enables it to execute jumps in various directions. Our innovative system is compact and designed for collecting environmental data in agricultural fields, regardless of whether the crops are newly planted or fully grown. The robot can maneuver by hopping from one location to another. Upon deployment in an area, it will immediately collect meteorological data from the environment, including temperature, pressure, altitude, and more. This data will then be transmitted to a cloud server for analysis. After completing data collection and analysis in one area of the field, the robot can hop to another area to continue gathering valuable information. Additionally, we collected data using this bio-inspired hopping robot and trained the dataset using machine-learning models for monitoring. With more data, this can be an autonomous hopping robot with intelligent sensing methodologies. Moreover, this proposed bio-inspired robot can be integrated with different sensors for innovative real-time applications.
Date of publication
Summer 7-10-2024
Document Type
Thesis
Language
english
Persistent identifier
http://hdl.handle.net/10950/4751
Committee members
Thesis Chair: Dr. Prabha Sundaravadivel, Ph.D, Member: Dr. Premananda Indic, Ph.D, Member: Dr. Matthew Vechione, Ph.D
Degree
Master of Science in Electrical Engineering
Recommended Citation
Kabir, Maliha, "BIO-INSPIRED ROBOTIC FRAMEWORK FOR SPATIOTEMPORAL ANALYSES IN ENVIRONMENTAL MONITORING APPLICATIONS" (2024). Electrical Engineering Theses. Paper 60.
http://hdl.handle.net/10950/4751