7 posts tagged with "use case"

Aircraft inspection is a complex task that demands high precision. These inspections often involve detecting subtle defects in aircraft components, such as cracks or dents.

There is a steady increase in the use of robots for aircraft testing, driven by their cost-effectiveness and the ability to reduce the error associated with manual inspections. However, the broader adoption of robotic systems has faced challenges, particularly the difficulty of accurately positioning robots within the complex environments of aircraft hangars, which lack GPS signals. Yet, accurate localisation is crucial for maintaining aircraft through meticulous and precise inspections.

Two students’ research projects at the Digital Aviation Research and Technology Centre at Cranfield University focus on enhancing the precision of robotic localisation in such conditions using two innovative methods, with the Husarion Panther UGV platform.

How can autonomous mobile robots help Australia, the heart of macadamia nuts, regain its position as the world's largest producer? And what do Husarion Panther UGV platforms have to do with it? As it turns out, quite a lot!

The Australian macadamia industry, facing many hurdles and challenges, has been overtaken by South Africa. Macadamia nuts are indigenous to Australia. Now, Australia has about 18-20% market share. Addressing the problem of food loss during harvesting, Royal Melbourne Institute of Technology (RMIT) developed a cutting-edge solution using the Husarion Panther UGV platform. This innovation aims to transform macadamia harvesting using advanced robotics to reduce waste and increase efficiency.

What inspired this RMIT project, and what technical challenges will they overcome? Dive into the details of this journey and the promising future of automated macadamia nut harvesting. 👇🏻

Autonomous navigation with real-time traffic analysis, supported by 5G technology and applied to the spacious mobile robot based on Husarion Panther. This is the combination that - starting from next year - will allow the myLOG system to deliver purchased goods right to the door of Strausberg residents, enabling them to order from local shops with door-to-door service.

Whizzy, as this is the name of an autonomous delivery robot developed by the consortium, has recently successfully completed its first test drive in the wild, demonstrating its capabilities and generating enthusiastic media coverage.

What is the motivation behind this project and what major challenges are yet to be faced by the platform constructors?

There is no greener industry than agriculture, right? While this claim may seem intuitive, current data reveals that land use related to agriculture contributes to as much as 10% of global CO2 emissions. With the escalating global climate crisis, the need to reduce agricultural emissions has become more pressing than ever.

But what if instead of drastically limiting emissions, we could just use the natural process of photosynthesis to address the challenge and actively remove CO2 from the atmosphere? Plants inherently capture carbon dioxide through photosynthesis, and the carbon they trap can be transformed into soil organic carbon - a phenomenon known as carbon sequestration.

Unmanned Aerial Vehicles (UAVs), also known as drones, are used nowadays in a wide variety of applications, exploring zones affected by natural disasters, surveilling, or transporting packages in urban areas. While drones provide opportunities previously unavailable, such as the ability to easily traverse rough terrain, quickly and efficiently explore unknown areas, and possess excellent communication capabilities, they also come with their own limitations. UAVs have a reduced flight time due to low battery capacity and cannot carry heavy payloads, including more powerful computers, heavy sensors, or manipulators.

These constraints can be overcome by developing cooperation between drones and Unmanned Ground Vehicles (UGVs), which offer higher payload and battery capacity. Simultaneously, UGVs can benefit from drones' greater range of sensors and higher traversability of difficult terrain. In scenarios where the drone and mobile robot cooperate to map and navigate unknown terrain, there is potential for achieving much higher efficiency in specific tasks, creating a whole new realm of possible applications.

We all know that limiting CO2 emissions is one of the most urgent goals we face today. But what if I tell you that, at this point, limiting emissions simply isn't enough, and we must also start actively removing CO2 from the atmosphere? What’s more, with regulations introduced in recent years, carbon removal is no longer just a matter of social responsibility, but it has become a business necessity for many companies. The price of emitting one tonne of CO2 is almost €95 in the European Union and $51 in the USA, creating both an ecological and business need to develop efficient carbon removal techniques. Unfortunately, most carbon removal techniques are expensive, do not generate financial profit for the companies and produce waste instead of a useful outcome.

But what if companies could remove carbon, thus reducing CO2 emissions, without incurring costs? What if they could actually use the removed carbon for something useful and profitable instead of discarding it? This idea stands behind the project of Rock-Farm, a business that provides services of carbon removal by… building rock walls. What’s even more interesting, they do it fully autonomously, using Panther as a base for their masonry robot.

Designing autonomous solutions for agriculture is not an easy task. While there are successful examples of robots autonomously planting, inspecting or picking more accessible crops, there is still a wide variety of fruits and vegetables that remain out of reach when it comes to autonomous harvesting. And there are reasons for that - agricultural environments can be harsh and extremely variable, posing the challenges both to the mechanical robustness of the robot platform and its abilities for autonomous navigation. Another problem to solve is implementing crop picking, which requires algorithms for efficient fruit localization, assessment of its ripeness and plucking without causing damage to the crop, which is especially demanding in case of fragile fruits.

All these challenges didn’t discourage members of EPFL CREATE Lab, who recently developed a proof-of-concept solution for harvesting raspberries, using Panther as a base for their mobile robot. Their novel approach allowed them to achieve 80% successful harvesting rate during the first field test. What was their key to success?