Author(s): Taylor Ripke, Kellen Reason, Tony Morelli
Published in: International Journal of Engineering Research & Technology
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Volume/Issue: Volume. 6 - Issue. 05 , May - 2017
Recent advancements in robotics and computer science are pushing the boundaries of exploration and our understanding of intelligent systems. These systems have the potential to interact with one another to solve difficult tasks, such as exploring a new planet or providing emergency assistance. Our research focuses on studying the interaction between an autonomous robot and drone and how they perceive and understand the environment to perform a given task. Utilizing advanced path-planning algorithms, image processing techniques, and various sensors for localization, the robot and drone can interact with the environment to solve generic tasks, such as finding an optimal path around a series of obstacles if the path is blocked utilizing a Greedy approach. Furthermore, the system is an adaptive learning model. The drone autonomously takes off and lands following the directions from the robot, increasing battery duration while providing the robot with additional sensory information. The robot and drone are two separate intelligent systems that work together solving different tasks utilizing the same dataset for learning and interacting.
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