Danny Eizicovits

Learn More
Developing robotic systems for selective harvesting is an important but challenging task due to the complicated nature of the task and the environment. Robotic selective harvesting comprises three major components: detection, grasping and manipulation. It is important in such a task is to embed perception capabilities within grasp planning and execution. To(More)
Robots for selective harvesting require efficient algorithms for planning path that end in high quality grasp-poses about the fruit. This paper presents Grasp Regions-Rapid exploring Random Trees (GR-RRT), a path planning algorithm that incorporates knowledge regarding grasp-poses quality. The algorithm includes offline fitting of a Gaussian mixture model(More)
  • 1