Smart farming technology is becoming of the actual topics in the modern world of technology. Contemporary farming technology expands robot applications by using AI for the recognition of variable patterns. Moreover, the agriculture field demands a safety robot, due to the fragile surrounded confined space and it must be adaptable to extremely constrained working environments. Therefore, this research paper presents a novel tomato harvesting robot arm based on a continuum robot structure. The proposed continuum robot arm flexible backbone structure provides safety and efficient work in a confined workspace. This research paper consists of three parts: the first part of the paper contains the robot design and the newly designed tomato harvesting gripper tool. The second part of the paper describes the machine learning part for detecting matured tomatoes and the distance measuring technique with a single camera. The third part of the research paper explains robot kinematics and control algorithms. The final part of the research paper explains the experimental results. As a result of the conducted experiment, the tomato harvesting speed of the proposed robot was 56 s for a single tomato. Meanwhile, the tomato recognition accuracy was 96 percent.
Wire-driven continuum manipulators are gaining more attention due to their flexibility and dexterity features. In comparison with traditional manipulators, the continuum structure is compliant and safe for human tissue and is able to easily adapt to the unstructured environment. Despite its advantages, wire-driven mechanisms have a serious problem with tension. While pushing and pulling, the wire loses tension, which leads to an ineffective way of driving the pulleys. Therefore, in this research, we propose a novel discrete continuum robot arm with a passive pre-tension mechanism that avoids the wire tension problem. Moreover, this paper will describe the backbone design of the discrete continuum arm and pre-tension mechanism structure, as well as forward and inverse kinematics and kinetic solutions, with simulation results.
Designing and development of agricultural robot is always a challenging issue, because of robot intends to work an unstructured environment and at the same time, it should be safe for the surrounded plants. Therefore, traditional robots cannot meet the high demands of modern challenges, such as working in confined and unstructured workspaces. Based on current issues, we developed a new tomato harvesting wire-driven discrete continuum robot arm with a flexible backbone structure for working in confined and extremely constrained spaces. Moreover, we optimized a tomato detaching process by using newly designed gripper with passive stem cutting function. Moreover, by designing the robot we also developed ripe tomato recognition by using machine learning. This paper explains the proposed continuum robot structure, gripper design, and development of tomato recognition system.