A robotic pruner ready to reduce production problems in apple orchards

Penn State University’s robotic pruner combines a three-rotation wrist end effector, which cuts branches, and a three-way linear manipulator that houses and moves the end effector to targeted pruning locations.
Photo courtesy of Penn State University

While all of agriculture is moving towards automation technologies, fruit tree production operations still require a fair amount of manual labor.

Pruning apple trees, for example, accounts for about 20% of total pre-harvest production costs. Between 30 and 35 hours of skilled labor are required per acre for hand pruning apple trees. The dilemma worsens as the labor force shrinks and labor costs rise.

“There is a need to find a potential solution to this problem,” said Azlan Zahid, a graduate student at Penn State University.

Zahid and his colleagues at Penn State designed the first robotic mechanism – an end-effector cutter – for a fully automated, computerized pruning system for modern apple orchards. To date, the concept of integrating such a robotic system based on Cartesian and rotary joints has shown promising results while overcoming difficult pruning conditions, he says.

Apple Tree Barriers

The complications that come with the concept of robotic pruning are largely due to the unstructured work environment an apple tree presents. The robotic cutting unit must be able to operate in tight spaces and reach targeted branches for pruning while avoiding the entanglement of other branches.

“Branches grow in a random orientation and direction, which basically causes difficulties for the reconstruction of the branches and also for the maneuvering of the system in the tree canopy,” says Zahid.

A second challenge concerns the spatial requirements of the maneuvering system. “Due to the complex architecture of the trees, there is very little space available in the tree canopy in which the robot can actually move and perform the operation,” says Zahid.

Movement violation

Zahid and his team (Md Sultan Mahmud, Long He, Dana Choi, Paul Heinemann and James Schupp) set out to develop a six degrees of freedom (DoF) pruning manipulator that meets maneuvering, spatial, mechanical and horticultural requirements . It is made up of two parts: a wrist effector – the cutter – which has three rotations (yaw, pitch and roll); and a three-way linear manipulator constructed to house the end effector and move it to targeted pruning locations.

To provide information for the design of the end effector, the researchers measured the cutting force of the branches with a sensor attached to the hand pruners. The part was then developed using three rotary motors and a pair of shear blade pruners powered by an electric gear motor (DC).

To guide the maneuvers of the end effector and the manipulator control, they developed an on-board microcontroller system with a user interface, using an interactive mathematical program that allows the calculations to be visualized. A mathematical model was developed for the simulation of workspace utilization, kinematic dexterity and reachable points for the end effector.

The apple tree was reconstructed using three-dimensional (3D) point cloud data by segmenting the tree trunk and primary branches. Multiple computer algorithms generate collision-free robot trajectories and find a smooth, optimized path to reach the targeted pruning locations.

Field studies

The researchers evaluated the performance of the prototype during field studies at Penn State’s Fruit Research and Extension Center in Adams County, Pennsylvania. Ten ‘Fuji’/Bud.9 trees were randomly selected from a trellis fruiting wall. Eight to 10 branches were selected from each tree.

The average time to reach the target branch was around 12-13 seconds. The robotic pruner successfully cut branches up to about 25 millimeters (mm) in diameter, which Zahid says is “well above the typical branch diameter range with the modern tree architecture system” .

“We were able to cut and reach all the branches we have in the trees,” he says. “And the path planning algorithms we developed successfully generated collision-free paths to reach the targeted pruning points.”

Machine vision required

There is room for improvement, notes Zahid. His team will add multiple approach angles to the system because it’s not possible for the cutter to hit perpendicular to the orientation of the branches every time due to the complex tree canopy, he says.

“We added several robot reach options (approach poses) in the computer program for this, which fundamentally improves the system’s ability to find the collision-free path reaching the target branches,” Zahid explains.

However, adding a large number of reach options may result in increased operation time as the robot searches for the path of the next or alternative approach option after the current approach fails, he said. This can be optimized, he adds, by using advanced computing techniques, such as parallel computing. By doing so, the robot can simultaneously search the trajectory of all approaches and then automatically select the optimal trajectory.

“As we used a LiDAR (light detection and ranging) sensor for the 3D reconstruction of the apple trees, some small/thin branches were missed by the LiDAR sensor due to the limitation of the resolution. In addition, the diameter of the branch could not be accurately measured, so it will be necessary to use an effective machine vision system, such as the use of an RGB-Depth (RGB-D) camera vision system to measure with precision the branch diameter in order to make automatic pruning decisions, because the diameter of the branches is one of the most important parameters for the selection of pruning branches,” explains Zahid.

Developing a pruning cut sequencing algorithm is also key to optimizing path lengths and cycle time for an efficient robotic pruning operation, he says.

“We need to incorporate a pruning cut sequencing algorithm, so we know which branch we need to cut first and which branch we need to cut second,” Zahid says. “We will basically integrate these two systems to develop a complete robotic pruning system.”



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