  There is a growing need for robotic apple harvesting due to decreasing
availability and rising cost in labor. Towards the goal of developing a viable
robotic system for apple harvesting, this paper presents synergistic
mechatronic design and motion control of a robotic apple harvesting prototype,
which lays a critical foundation for future advancements. Specifically, we
develop a deep learning-based fruit detection and localization system using an
RGB-D camera. A three degree-of-freedom manipulator is then designed with a
hybrid pneumatic/motor actuation mechanism to achieve fast and dexterous
movements. A vacuum-based end-effector is used for apple detaching. These three
components are integrated into a robotic apple harvesting prototype with
simplicity, compactness, and robustness. Moreover, a nonlinear velocity-based
control scheme is developed for the manipulator to achieve accurate and agile
motion control. Test experiments are conducted to demonstrate the performance
of the developed apple harvesting robot.
