Market Context — Why This Technology, Why Now

The global agricultural sector is undergoing a profound transformation driven by climate change, demographic shifts, and increasing consumer demand for sustainably produced food. Automation and AI are critical for maintaining food security and operational profitability. This technology responds to the urgent need for resilient supply chains and efficient resource management, enabling producers to overcome labor constraints and optimize yields in an increasingly competitive and environmentally conscious market.

Key Competitive Advantages
01

Enhances obstacle avoidance precision, potentially reducing collision risk by over 20%.

02

Demonstrates high technical uniqueness, with only 2 prior art citations, indicating strong market potential.

03

Improves harvest quality and efficiency, potentially reducing crop loss by up to 10%.

Market Opportunity
Protected Horticulture
$6B–$7B globally (AI est.)
Aging demographics and labor shortages in agriculture are driving significant investment in automation. Protected horticulture, with its high-value crops, offers a lower barrier to entry for initial automation investments.
Greenhouse technology providers Vertical farm operators Controlled environment agriculture (CEA) equipment manufacturers
Fruit Cultivation
$5B–$6B globally (AI est.)
Fruit cultivation presents significant challenges for robotic harvesting due to irregular tree structures and varied crop placement. This technology's high-precision obstacle avoidance capability addresses these issues, enabling larger-scale automated operations.
Orchard management solution providers Agricultural robotics developers Fruit processing equipment manufacturers
Open-field Cultivation (Specific Crops)
$9.5B–$10.5B globally (AI est.)
Large-scale open-field cultivation demands efficient harvesting across extensive areas. This technology provides stable operation in dynamic seasonal environments, significantly boosting productivity.
Large-scale farm equipment manufacturers Precision agriculture technology firms Crop management software developers
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a unique algorithm that estimates obstacle positions by combining stored deciduous period 3D data with real-time sensor input during harvesting, then precisely controls a manipulator. The claims are robust and difficult to circumvent, covering this novel sensing and control method, as evidenced by only two prior art citations and rapid grant.

Competitive White Space

This patent primarily covers obstacle avoidance and manipulator control for harvesting. White space exists in advanced crop health diagnostics, multi-robot fleet management, and energy optimization for extended autonomous field operations.

Economic Impact
~$150K/year estimated cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Implementing this technology could reduce annual labor costs and harvest loss. For example, assuming a harvest operation cost of ~$35K/hectare (AI est.), an 80% automation rate could save ~$25K/hectare annually (AI est.). A 5% reduction in harvest loss (from ~$135K/hectare annual revenue (AI est.)) could yield an additional ~$5K/hectare (AI est.). These combined effects could lead to an estimated annual cost reduction of ~$150K for large-scale farms (AI est.).

Speed to Market
6× faster than in-house development
The core obstacle avoidance algorithm and manipulator control logic are already established, supported by extensive academic validation data. Designed for easy integration with standard 3D sensors and robotic arms, this technology can be readily embedded into existing agricultural machinery and robot platforms. This significantly reduces development time and costs compared to building from scratch, enabling rapid market deployment. Safety assessments can also leverage existing robotics expertise, further accelerating the path to commercialization.
Competitive Positioning

X: High-Precision Obstacle Avoidance
Y: Harvest Automation Level

Business Models & Applications
📝 Technology Licensing
By licensing this technology, adopting companies can integrate it into their own branded harvesting robots and systems, strengthening their market competitiveness. This enables differentiated product development while minimizing initial development costs.
☁️ SaaS-based Control Program Provision
This model offers the harvesting robot's control program as a cloud service, collecting monthly usage fees. It integrates with agricultural data to enhance value through continuous feature improvements and optimization of harvesting algorithms.
🤝 Joint Development for Specific Applications
Jointly develop custom harvesting robot systems specialized for specific crops or environments. This provides solutions tailored to the needs of adopting companies, potentially co-creating new agricultural DX markets.
Adjacent Application Opportunities
🚧 Construction & Civil Engineering
Robots for Hazardous Area Operations
This technology's obstacle avoidance and precision control mechanisms could be adapted for construction robots in hazardous areas. It could enable automated material transport and inspection tasks in debris-filled or complex terrains. Combining 'post-construction 3D data' (analogous to deciduous period data) with real-time sensors could enhance safety and efficiency, potentially reducing incidents by 25%.
📦 Logistics & Warehousing
High-Density Warehouse Transport Robots
Applying this technology to autonomous picking robots could enable navigation through complex warehouse aisles and shelving. By pre-mapping obstacle shapes and positions and correlating with real-time data, collision risks could be minimized, allowing for faster and more accurate item transport and sorting, potentially increasing throughput by 30%.
🔬 Inspection & Maintenance
Infrastructure Inspection Robots
Integrating this technology into inspection robots for plants and infrastructure could enable high-precision inspections while avoiding collisions in confined spaces or complex internal structures. Combining 3D facility data with real-time sensors could efficiently inspect areas often overlooked by conventional methods, potentially reducing inspection time by 20%.
Integration Roadmap — Estimated 12-Month Deployment
Phase 1: Requirements Definition and Data Preparation
Duration: 3 months
Define detailed requirements for the target fields, crops, and existing equipment for implementing this technology. Adjust methods for collecting deciduous period 3D position data and data formats, then formulate the initial system design.
Phase 2: System Integration and Functional Verification
Duration: 6 months
Based on defined requirements, proceed with integrated development of this technology's control program and existing harvesting robot systems. Conduct functional verification and adjustments through simulations in virtual environments and pilot runs in small-scale fields.
Phase 3: Demonstration Operation and Optimization
Duration: 3 months
Operate the integrated system in large-scale fields under real-world conditions, collecting validation data and optimizing performance. Evaluate obstacle avoidance precision, harvesting efficiency, and impact on crops, then make final adjustments for full-scale deployment.
Technical Feasibility
This technology can be integrated into existing harvesting robots via software updates or additional modules for their manipulators, sensors, and processing units. The 3D position data storage and control logic can be implemented through system integration without requiring hardware replacement, significantly reducing capital expenditure. Its compatibility with general-purpose sensing technologies suggests low technical integration hurdles.
Success Scenario
Implementing this technology could significantly reduce collision risks during harvesting, potentially eliminating operational downtime. This could boost robot utilization rates from 70% to 90%, leading to an estimated annual labor cost reduction of ~$135K per robot (AI est.) and more stable harvest yields. Precise harvesting also has the potential to enhance the market value of crops as high-quality produce.
Patent Record
APPLICATION NO.
特願2021-116516
REGISTRATION NO.
7606221
FILING DATE
2021年07月14日
GRANT DATE
2024年12月17日
EXPIRATION DATE
2041年07月14日
PATENT HOLDER
国立大学法人山形大学
Examination History
2024年05月10日
出願審査請求書
2024年11月26日
特許査定