Simulation of Apple Picking Path Planning Based On Artificial Potential Field Method

Xie, Junlin; Zhang, Zhiyong; Wei, Ziyi; Ma, Saiwei

doi:10.1088/1755-1315/252/5/052148

Cited by 4 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Robot fruit harvesting problems typically require planning the motion of a high-DOF robot arm from its initial configuration to the fruit position through a cluttered environment. We can either plan the robot's path in the workspace [12], [13] and then map it to the configuration space (C-space) of the robot, or directly plan in the C-space [11], [17], [20].…”

Section: A Motion Planning For Fruit Harvestingmentioning

confidence: 99%

“…This motivates us to consider RRT-based approaches for the lime picking task. While most approaches for fruit harvesting only consider the main stem, branches or other fruits as obstacles [6], [14]- [17], they do not account for collision with the leaves. If the robot ignores the leaves, it could potentially damage the plant foliage.…”

Section: A Motion Planning For Fruit Harvestingmentioning

confidence: 99%

“…Previous work also avoids collision with the leaves [11] or models the plant foliage as a cylinder that must be entered radially [12], [13]. However, the majority of prior work does not consider the leaves at all [6], [14]- [17]. This is reasonable when the fruit is well separated from the plant foliage, but in the case of lime trees and many other important subtropical and tropical tree crops, the fruits are often engulfed by leaves [18].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robotic Lime Picking by Considering Leaves as Permeable Obstacles

Nemlekar¹,

Liu²,

Kothawade³

et al. 2021

Preprint

View full text Add to dashboard Cite

The problem of robotic lime picking is challenging; lime plants have dense foliage which makes it difficult for a robotic arm to grasp a lime without coming in contact with leaves. Existing approaches either do not consider leaves, or treat them as obstacles and completely avoid them, often resulting in undesirable or infeasible plans. We focus on reaching a lime in the presence of dense foliage by considering the leaves of a plant as permeable obstacles with a collision cost. We then adapt the rapidly exploring random tree star (RRT*) algorithm for the problem of fruit harvesting by incorporating the cost of collision with leaves into the path cost. To reduce the time required for finding low-cost paths to goal, we bias the growth of the tree using an artificial potential field (APF). We compare our proposed method with prior work in a 2-D environment and a 6-DOF robot simulation. Our experiments and a real-world demonstration on a robotic lime picking task demonstrate the applicability of our approach.

show abstract

Section: A Motion Planning For Fruit Harvestingmentioning

confidence: 99%