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Trimble experts share their predictions for autonomous technology in 2023, and what’s next for key industries

As the proverbial ball drops on 2023, we asked some of Trimble Autonomy’s brightest minds — including product strategists and engineers — for their thoughts around where autonomous tech is headed this coming year and beyond. Here are 10 of their top predictions for agriculture, construction, automotive and more:


“Labor constitutes up to 40% of the operating expense in some specialty crops in California and it is only expected to grow. The lack of skilled labor and a fast aging farming population is accelerating the need for robotics and automation of specialty crop workflows. Several purpose built robotic companies are being funded to address these challenges ranging from automated weeding, to spot spraying to crop picking/harvesting that are poised to transform the way farming is done.”

—Giri Baleri, director of product management - strategic marketing, off-road

“Usage of automation in agriculture has been increasing in the last couple of decades and is expected to continue to grow because of challenges including population growth, disruptions due to climate change, shortage of skilled workforce and short windows to complete tasks. Many companies including startups are investing in the development of precision farming technology, which includes advanced guidance technologies, self-driving technologies, agricultural drones, robotics, advanced sensing technologies, etc. There is also increasing demand for intelligent or smart farming technologies, which use smart sensors, drones, data analytics to optimize resource usage (water, fertilizer, pesticides, etc.), to increase productivity and decrease the environmental impact of farming. From large fields to greenhouses with vertical farming, these technologies can have considerable impact on improving efficiency and yields and cost savings, when used appropriately.”

—Vinnee Selvi, vehicle controls engineer

“In viticulture and orcharding, using autonomous tech to react is increasing significantly in order to treat diseases quickly and efficiently. More and more, holistic precautionary spraying in advance is decreasing in order to meet legal requirements to save chemicals, on the one hand, and to save plant protection products and costs, on the other. In addition, spraying is more effective in the evening or at night (due to less wind and sun). The ability to react is then decisive. However, as there is less and less trained and willing agricultural staff available, the pressure for autonomous solutions will increase. Especially in the vineyards and orchards, autonomous vehicles could be more likely to be used in some countries, as fields are usually bordered by fences and bushes and therefore more secure.”

—Christoph Thiele, product manager, agriculture

“In 10-15 years, the landscape of autonomy in agriculture will be quite different and transformational. These changes will be driven by the limitations of today in energy availability, lack of nutrition-rich soil, lack of usable water, negative impact of climate change, time availability, labor availability, etc., coupled with a yearning for efficiency. My vision of that change presents itself as a swarm of small-sized robotic machines (on land and in air) that are capable of planning like humans to, responding rapidly to unforeseen situations, disperse themselves in fields to do highly precise operations that are sustainable based on decisions made, and come back to dock, charge or service themselves.”

—Gayatri Sukumar, engineering management, agriculture 


“The need for safety, sustainability and doing more with less continues to grow. At the same time there is a serious concern around skilled construction retiring, while attracting new young workers into construction is difficult due to old perceived construction personas. This is a real dilemma because construction demands are not slowing down. Companies cannot get the workers they need, let alone skilled workers. The good news is technology can help. Full autonomy in construction will take time (years). But the adoption of technology that excites the emerging workforce, and demand for ‘operator assistance’ and ‘safety’ features, will grow and be relied upon. Autonomous technology stands to help solve this very real dilemma.”

Cameron Clark, earth moving industry director

“Autonomous progression in construction is a journey, and there’s clear value in bringing task-oriented assistive technologies of levels 1 and 2 — like automatic steering and blade control — to operators in the cab. But without the ability to link it all together for end-to-end digital workflows, customers will end up with essentially a black box that requires more time than necessary to tell machines what to do. Getting the intended productivity benefits and cost savings out of it will require collaboration from partners with proven success creating autonomy, and the industry knowledge to ensure solutions meet workflow needs. That’s the money side of autonomy, and it’s a critical piece of the puzzle. Level 5 might be a long way out, but obstacle detection, radar/lidar, sensors, cameras — all that is already setting the bar higher for safety and productivity, and smooth implementation with the ability to evolve is something customers need today.”

—Geoffrey Kirk, Product manager autonomy/construction

“By late 2023, we expect to see AI in the market for use in all major autonomy stack components at the edge, from planning to perception to controls, with multiple networks cross checking each other for accuracy and expected performance tradeoffs. Beyond that, some trends we see on the horizon include 4D or imaging radar beginning to displace lidar as the preferred sensor for high fidelity perception systems, due to improved cost and robustness in adverse weather conditions. Also, look for industry standard interfaces to become available in construction, allowing platform-agnostic cloud planning intelligence and work-order execution in real time.”

—Brandon Sights, engineering director, autonomy


“In automotive there are two principal challenges to overcome. First, precise absolute positioning in all GNSS denied or obscured environments and second, crowdsourcing of precise maps using passenger or shared mobility vehicles and not ones dedicated solely for mapping. Precise absolute positioning is defined as lane level or 10cm precision. Achieving that in all facets of a typical drive from freeway to downtown corridor and underground is essential. Adding to this requirement is the need for ASIL certification (not only of the onboard software but also the correction source and integrity of the measurement). New techniques such as map based localization (MBL) are critical to that process and fusing sensor data to derive a position as a source of corrections. Maps can only be used if they are current to achieve this. Therefore a continuous stream of data from road vehicles is required to update maps, current road conditions, etc., for complete situational awareness.”

—Louis Nastro, director, product management - strategic marketing, on-road

“Past optimisms on the mass deployment of fully autonomous vehicles by current times have consistently fallen short. On-road Level 4/5 autonomy is very hard, and expensive. While the bigger players in autonomous driving will continue to deploy their fleets in selective service areas to transport people or goods, an increasing number of smaller players will pivot to alternative applications and markets, including agriculture and construction. Sensing hardware technologies for autonomy will not likely have any major disruptors in the near future, thus increasing the reliance on software solutions. Navigation (i.e., mapping and localization) and perception software based on deep neural networks will continue to have an increasing appetite for (real and high-fidelity simulation) data as the demand to operate in new environments and adverse environmental conditions continuously generate new corner cases. For navigation using non-machine learning approaches, scalability will be the key to success.”

—Keith Leung, engineering management, autonomy


“The convergence of greater data capacity of 5G, high precision location data over cellular and evolving artificial intelligence models will push greater efficiencies and accuracies in real time based applications. The ability to feed highly accurate location data into artificial intelligence models will be a game changer for enterprise application developers, as now high-accuracy location applications will be available to mass markets on smartphones without the need of external antennas. Situational awareness and augmented reality applications will likely be the first foothold for smartphone deployments and industrial verticals will be the first adopters. Artificial intelligence models that merge data analytics of lidar, precise location data and video will create safer autonomous driving and delivery applications that will reduce insurance rates, delivery costs and provide more efficient shipping schedules.”

—Arn Hayden, business development manager, positioning services