We use cookies to enhance your experience. By continuing to browse this site you agree to our use of cookies. More info.
The planetary rovers that assist humans in exploring other planets have the potential to stray from their intended course or become stranded when they slip on loose terrain. Researchers at the Shibaura Institute of Technology have created a revolutionary technology that allows rovers to identify their slip condition based on changes in the shape of their chassis to address this issue. Inspired by human muscles, this innovative technique may lead to more sophisticated sensing technologies that improve the safety of autonomous vehicle travel.
Similar to how human muscles detect the traveling state of the body, the slip condition of rovers can be determined by detecting the deformation of their chassis. This technology can be used to prevent the slipping of rovers. Image Credit: Kojiro Iizuka from Shibaura Insititute of Technology
Unmanned rovers are essential for exploring planets and moons because of the extreme conditions found in these regions. The understanding of these alien worlds has benefited significantly from NASA’s Mars and lunar exploration rovers. The terrain on planetary surfaces is frequently difficult, featuring dunes, craters, and slopes.
More importantly, rover mobility is severely hampered by the regolith, which is a fine powder covering these surfaces. The rovers’ ability to skid on these uneven surfaces can impede their advancement and potentially compromise their missions.
Numerous techniques have been investigated to identify the traveling state or slip condition of rovers, most of which rely on visual data from cameras. These techniques do have some drawbacks, though, as they might not be able to discern between distinct topographical elements, including boulders and loose sand.
The rovers can find a way to solve this issue by learning more about the traction on each wheel. In this manner, the rover could recognize its traveling condition more quickly and adjust its stance to prevent slipping.
This has been made possible by the recent development of a novel system by Professor Kojiro Iizuka of the Department of Machinery and Control Systems of the College of Systems Engineering and Science at Shibaura Institute of Technology (SIT), Japan, and Dr. Kohei Inaba of SIT. This system enables a rover to detect its traveling state by a change in the shape of its chassis.
Remote Sensing published the findings on August 30th, 2023.
Nuclear chain fibers and nuclear bag fibers are unique muscle fibers found in human muscles that aid in the detection of the body’s moving status. The nuclear chain fibers assist in identifying the body’s static posture by detecting changes in muscular tension. Nuclear bag fibers, on the other hand, measure how quickly muscle fibers stretch and assist in determining the body’s dynamic state.
Drawing comparisons with human muscles, the researchers classified the rover’s change in shape, manifested as strain, into two categories: displacement of strain and vibrational shift in strain. They analyzed strain displacement data with nuclear chain fibers and strain velocity with nuclear bag fibers.
According to the nuclear chain fiber study, the forces acting vertically and in the direction of the rover's motion altered with strain. Monitoring strain variations can thus enable the detection of force changes, revealing the rover’s traveling condition.
Furthermore, the researchers discovered that the rate of strain change may successfully evaluate the extent of slippage and consequent changes in the rover’s travel condition using nuclear bag analysis. Using this information, the system can determine the rover’s state in real-time, allowing the rover to make necessary moves to avoid slipping incidents.
The study also underlines the system’s ability to detect environmental impediments such as pebbles and stones, emphasizing its potential to improve rover safety and efficiency.
During rover route planning, the experiences from this study should be considered to ensure that the rovers can travel safely. These findings represent the first step towards incorporating elements of biological functionality in sensing moving objects. We believe that our approach will also be effective for unmanned aerial vehicles and automatic driving in the future.
Kojiro Iizuka, Professor, Department of Machinery and Control Systems, College of Systems Engineering and Science, Shibaura Institute of Technology
Finally, this new study represents a huge step forward in increasing the safety and effectiveness of rover missions, promising advances in the study of other planets and celestial bodies.
Iizuka, K., et al. (2023) Slip Estimation Using Variation Data of Strain of the Chassis of Lunar Rovers Traveling on Loose Soil. Remote Sensing. doi:10.3390/rs15174270.
Source: https://www.shibaura-it.ac.jp/en/
Do you have a review, update or anything you would like to add to this news story?
Cancel reply to comment
As part of an Editorial short series, AZoRobotics takes a look at how the renewable energy sector is harnessing the power of robotic technologies. Here, we take a look at robots in hydropower stations.
Amid the rapid global expansion of the wind energy sector, the integration of robotics is becoming pivotal for wind farm operators.
Like any renewable energy infrastructure, solar plants must be protected and secured. It is here where robots and autonomous systems can come into play.
Discover Cavitar’s welding cameras that can be used in a variety of situations to offer high-quality visualization of the welding processes.
MTI’s 1510A portable signal generator and calibrator is ideal for testing the integrity of sensor signal conditioning electronics.
Using the advantages of the phased array technology, Olympus has designed a powerful inspection system for seamless pipe inspections well-adapted to the stringent requirements of the oil and gas markets. This phased array system is flexible and can be used to match inspection performances and the product requirements of customers.
AZoRobotics.com – An AZoNetwork Site
Owned and operated by AZoNetwork, © 2000-2023
