Apple fruitlet thinning is critical in cultivating high-quality apples, requiring an expert workforce to manage the orchard. The thinning process requires precise mapping of fruitlet clusters across the tree branches to manage the desired load for each tree. This paper presents Archie Snr, which was developed to autonomously assess the current load of the tree and thin the excess apples as an expert thinner would. The platform has been extensively evaluated in a real-world commercial orchard. The results show the platform can generate an average load count accuracy of 82.1% with a recall of 93.3%. The system was then able to successfully thin 66.14% of the fruitlets from the canopy.

Cane pruning grapevines is a complex manual task requiring expert vine assessment to determine which canes to prune. This paper presents Archie Jnr, which was developed to autonomously assess the structure of the vine and prune the lower-quality canes as an expert pruner would. The platform has been extensively evaluated in a real-world commercial vineyard using a three-cane pruning method. The results show the effectiveness of the vision system for generating accurate assessments of a vine’s canes. The platform is also shown to be capable of successfully pruning 71.1% of the 311 total canes that required pruning across 25 vines.

Aotearoa New Zealand has a strong and growing apple industry but struggles to access workers to complete skilled, seasonal tasks such as thinning. To ensure effective thinning and make informed decisions on a per-tree basis, it is crucial to accurately measure the crop load of individual apple trees. However, this task poses challenges due to the dense foliage that hides the fruitlets within the tree structure. In this paper, we introduce the vision system of an automated apple fruitlet thinning robot, developed to tackle the labor shortage issue. This paper presents the initial design, implementation, and evaluation specifics of the system. The platform straddles the 3.4 m tall 2D apple canopy structures to create an accurate map of the fruitlets on each tree. We show that this platform can measure the fruitlet load on an apple tree by scanning through both sides of the branch. The requirement of an overarching platform was justified since two-sided scans had a higher counting accuracy of 81.17% than one-sided scans at 73.7%. The system was also demonstrated to produce size estimates within 5.9% RMSE of their true size.

This paper presents a control strategy for the pursuer in the pursuit-evasion game problem when the evader behaves intelligently. The pursuer in the proposed technique does not try to react to the evader's behavior instantaneously. The proposed technique therefore does not yield instantaneous optimality but capture the evader in a time-efficient and robust fashion even when the evader is intelligent. The proposed technique was applied to two numerical examples and the results were compared to those by the conventional motion tracking algorithms. The results and comparison show that the proposed technique could capture the evader faster than the conventional motion tracking algorithms in both the examples.