This paper presents an optimization approach for generating custom manipulator configurations using a proposed unconventional modular library. An end-to-end solution is presented in which the resulting optimal models of the modular compositions can be integrated directly with the Robot Operating System platform. The approach utilizes an unconventional modular library, which is adaptable to a wide range of parameters for customization including non-parallel and non-perpendicular joint axes, and the unified modeling technique for getting the custom modular configurations. The single objective function optimization problem is formulated based upon the discrete parameters of reconfiguration depending upon the available modular library such as, number of joint modules, skew-twist angle, intersecting-twist angle, connection ports of the module, module size, modular sub-assembly unit and curved links. Two case studies, including an application to the agricultural vertical farms, are presented to validate the results.

The Modular Automated Crop Array Online System (MACARONS) is an extensible, scalable, open hardware system for plant transport in automated horticulture systems such as vertical farms. It is specified to move trays of plants up to 1060mm x 630mm and 12.5kg at a rate of 100mm/s along the guide rails and 41.7mm/s up the lifts, such as between stations for monitoring and actuating plants. The cost for the construction of one grow unit of MACARONS is 144.96USD which equates to 128.85USD/m2 of grow area. The designs are released and meets the requirements of CERN-OSH-W, which includes step-by-step graphical build instructions and can be built by a typical technical person in one day at a cost of 1535.50USD. Integrated tests are included in the build instructions are used to validate against the specifications, and we report on a successful build. Through a simple analysis, we demonstrate that MACARONS can operate at a rate sufficient to automate tray loading/unloading, to reduce labour costs in a vertical farm.

With the global demand for food escalating, vertical farms are becoming a critical component of agriculture's future. They use robotics, machine learning and artificial intelligence (AI) to automate farming and perfect the growing of greens and vegetables. With steady growth, the vertical farming market was had an estimated value of $4.4 billion in 2019 and is expected to reach $15.7 billion by 2025. Fifth Season, a vertical farm in Pittsburgh with $35 M in funding, uses super-stack software and robotics to run their fully automated farming systems. And, by combining big data and AI, they have created the optimal grow recipe that determines the best flavor for the plants they grow.

I refer to the Opinion piece "How AI can strengthen food resilience" (March 17). While I appreciate that artificial intelligence (AI) can help to strengthen Singapore's food resilience, I am disappointed that the authors did not also provide its limitations, and more importantly, other critical factors that can severely impact Singapore's food resilience. Take Singapore's vertical farms for vegetables and fish as an illustration. These vertical farms are energy intensive. Indoor plants need artificial lighting and environment control; indoor fish farms, otherwise known as recirculating aquaculture systems, need recirculating pumps, filtration systems, oxygenation systems, and so on, all of which are energy intensive.

In the hills between Kyoto, Osaka and Nara prefectures, surrounded by technology companies and startups, Spread Co. is preparing to open the world's largest automated leaf-vegetable factory. It's the company's second vertical farm and could mark a turning point for vertical farming -- keeping the cost low enough to compete with traditional farms on a large scale. For decades, vertical farms that grow produce indoors without soil in stacked racks have been touted as a solution to rising food demand in the world's expanding cities. The problem has always been reproducing the effect of natural rain, soil and sunshine at a cost that makes the crop competitive with traditional agriculture. Spread is among a handful of commercial firms that claim to have cracked that problem using a mix of robotics, technology and scale.

Back in the good old days, farming was easy. Throw some seeds in the ground, keep it watered, pray to your preferred deity to spare your crops from pestilence and wait for harvest season. But with the global population closing in on 7 billion mouths to feed, humanity is going to have to figure out how to grow more food using less land and fewer resources, and soon. So while some researchers and equipment manufacturers are devising intelligent agricultural implements that will toil in tomorrow's fields on our behalf, others are aiming to bring futuristic farms to urban city centers. "Over three billion dollars were lost in California alone [in 2017], because there's not enough people to actually do the operations in seeding or harvesting," Brandon Alexander, co-founder of Iron Ox Robotic Farms, told Engadget.

From a first-principles perspective, the task of feeding eight billion people boils down to converting energy from the sun into chemical energy in our bodies. Traditionally, solar energy is converted by photosynthesis into carbohydrates in plants (i.e., biomass), which are either eaten by the vegans amongst us, or fed to animals, for those with a carnivorous preference. Today, the process of feeding humanity is extremely inefficient. If we could radically reinvent what we eat, and how we create that food, what might you imagine that "future of food" would look like? The average American meal travels over 1,500 miles from farm to table.