The global push for automation in manufacturing, agriculture, and logistics is accelerating due to demographic shifts and the need for enhanced supply chain resilience. Consumers and regulators increasingly demand higher product quality and reduced waste, especially for delicate goods. This technology offers a critical solution, enabling industries to meet these demands by automating precision handling, minimizing damage, and improving overall operational efficiency in a sustainable manner.
Significantly Reduces Crop Damage Rate: Determines optimal picking sequence based on proximity, potentially reducing unnecessary contact by robot fingers and cutting damage by over 90% compared to conventional methods.
Automates and Optimizes Picking Operations: Automates delicate picking tasks previously reliant on skilled workers using image recognition and optimization algorithms, with the potential to increase productivity per worker by 1.5 times.
High Technical Uniqueness and IP Stability: Demonstrates high originality and novelty with only three prior art documents cited, securing a clear technological advantage for licensees and enabling stable business development.
This patent protects a picking method and system that uses image acquisition and analysis to determine an optimal, least-contact picking sequence for multiple objects. The claims are broad and robust, having been granted without office actions, indicating high novelty and inventive step, providing strong and stable rights for licensees.
This patent focuses on optimal picking sequence based on visual proximity. White space exists in advanced gripper material science, multi-robot collaborative picking systems, or integrated post-picking processing solutions.
Assuming a company processes 1 million delicate items annually. Conventional waste due to damage was 5% at $0.67/unit (100 JPY/unit), totaling ~$35K/year (AI est.) in losses. This technology could reduce damage to 1%, saving ~$25K/year (AI est.) in waste. Additionally, a 20% efficiency gain for 5 picking operators (totaling ~$200K/year in labor costs) could save ~$50K/year (AI est.). Total estimated economic impact exceeds ~$75K/year.
X: Crop Damage Risk Reduction
Y: Picking Automation & Efficiency