Frontier Research Overview
“Traditionally, the inspection of pipelines has been done by inspectors checking the pipes. This can be erroneous, time-consuming, and labor-intensive.”
To overcome the problem, different types of mobile robotic systems for the inspection have been developed. However, existing robots still have several limitations, e.g., lacking versatility, energy efficiency, and adaptability. We therefore aim to develop intelligent robotic inspection systems with versatility, energy efficiency, and adaptability for effective remote inspection of pipelines in the oil and gas industry.
Chaotic Neural Oscillator for Navigation and Exploration of Autonomous Drones
Efficient exploration in unknown environments (e.g., indoors, caves, and tunnels) is an important basic behavior of autonomous drones for complex missions (e.g., indoor exploration, search and rescue, and goal-directed navigation). In such missions, the drones need to explore the overall area as much as possible within a short or given period. Typically, exploration control uses (Gaussian) random walk. This control technique may lead to undesired behavior, such as overturning or looping. It causes the drone to repeatedly explore the same spots; thereby having difficulty covering the overall area. To overcome this problem, we propose here the use of a chaotic neural oscillator for efficient exploration of autonomous drones instead of Gaussian random walk. This technique is inspired by the chaotic (nonrandom) behavior of fruit flies, giving them efficient food searching. We combine the chaotic neural oscillator (acting as our exploration control module) with reflex-based neural control for obstacle avoidance. By doing so, the drone is able to autonomously
perform efficient exploration (covering the area larger than an exploratory random-walk strategy) in an autonomous and safe manner.
For more details, see _____ (wait for the published link)
Presentation Video link: https://youtu.be/ulbdMoYv3rQ
iCrawl: An Inchworm-Inspired Crawling Robot for Pipe Inspection:
Inchworms use their morphology and evolved behaviors to crawl and climb various complex surfaces. This has inspired the development of different robots that can demonstrate similar capabilities for various applications such as the inspection of a complex environment. One of the key challenges in designing these robots is to enable them to be practically deployable with a compact design for providing continuous adaptability to a complex terrain such as an outer-pipe surface. Taking this into consideration, we present a new design for an inchworm-inspired crawling robot (iCrawl). The 5 DOF robot relies on two legs; each with an electromagnetic foot, in order to crawl on the metal pipe surfaces. The robot uses a passive foot-cap underneath an electromagnetic foot, enabling it to be a versatile pipe-crawler. The foot-cap design is an abstraction of the leg posture in an inchworm adapting to a round surface. The proposed foot-caps give the robot adaptability and stability for crawling on metal pipes of various curvatures. A state-machine based controller was developed to produce the required motor signals for the two inchworm-inspired crawling gaits: i) the step gait, and ii) the sliding gait. Both gaits were tested on the robot, eventually leading to it effectively crawling on the pipes and flat surfaces, climbing a metal wall and a pipe, and succeeding in obstacle avoidance during crawling. Experimental results also show that the robot has the ability to crawl on the metal pipes of various curvatures using the foot-caps and an appropriate gait. The robot can be used as a new robotic solution to assist close inspection outside the pipelines, thus minimizing downtime in the oil and gas industry.
For more details, see Khan, et al., IEEE Access, 2020.
Video link of robot experiments: