Soft manipulator robot for selective tomato harvesting

Mohamed, Abdulla; Shaw-Sutton, J.; Green, B.M.; Andrews, W.F.P.; Rolley-Parnell, Emily-Jane; Yuan, Zhulin; Zhou, Ping; Mao, Xiaofeng; Fuller, Michael P.; Stoelen, Martin F.

doi:10.3920/978-90-8686-888-9_99

Cited by 14 publications

(6 citation statements)

References 7 publications

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“…Other research in the same group at the University of Plymouth used the technology for developing selective harvesting tomatoes and raspberries. See for example (Mohamed et al, 2019 ).…”

Section: Resultsmentioning

confidence: 99%

“…However, the low tolerances of assembly and the flexibility of the plastic pieces themselves means the accuracy of the kinematic model of the arm, which assumes rigid bodies, is degraded with external loading or poses perpendicular to gravity. Thus, any tasks demanding a high absolute accuracy of the gripper requires an approach to compensate for this, for example using visual servoing with gripper-mounted cameras (Mohamed et al, 2019 ). Furthermore, the Dynamixel servos provide a relatively slow and inaccurate reading of the load on the servo, which makes estimating forces and torques difficult to do in real-time.…”

Section: Discussionmentioning

confidence: 99%

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The GummiArm Project: A Replicable and Variable-Stiffness Robot Arm for Experiments on Embodied AI

et al. 2022

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Robots used in research on Embodied AI often need to physically explore the world, to fail in the process, and to develop from such experiences. Most research robots are unfortunately too stiff to safely absorb impacts, too expensive to repair if broken repeatedly, and are never operated without the red kill-switch prominently displayed. The GummiArm Project was intended to be an open-source “soft” robot arm with human-inspired tendon actuation, sufficient dexterity for simple manipulation tasks, and with an eye on enabling easy replication of robotics experiments. The arm offers variable-stiffness and damped actuation, which lowers the potential for damage, and which enables new research opportunities in Embodied AI. The arm structure is printable on hobby-grade 3D printers for ease of manufacture, exploits stretchable composite tendons for robustness to impacts, and has a repair-cycle of minutes when something does break. The material cost of the arm is less than $6000, while the full set of structural parts, the ones most likely to break, can be printed with less than $20 worth of plastic filament. All this promotes a concurrent approach to the design of “brain” and “body,” and can help increase productivity and reproducibility in Embodied AI research. In this work we describe the motivation for, and the development and application of, this 6 year project.

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“…Other research in the same group at the University of Plymouth used the technology for developing selective harvesting tomatoes and raspberries. See for example (Mohamed et al, 2019 ).…”

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The GummiArm Project: A Replicable and Variable-Stiffness Robot Arm for Experiments on Embodied AI

et al. 2022

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“…This research has become a hot topic and has great potential advantages in flexible and adaptive operations in agriculture. Mohamed et al [142] have developed a soft robotic arm that used agonist-antagonist actuators connected to the joints via flexible tendons for tomato harvesting. Using elastic silica gel as material, Bartlett et al have designed a soft robotic hand with a pneumatic network as an actuator [143] .…”

Section: Soft Agricultural Robot Technologymentioning

confidence: 99%

Development status and trend of agricultural robot technology

Jin¹,

Liu²,

Xu³

et al. 2021

International Journal of Agricultural and Biological Engineering

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In the face of the contradiction between the increasing demand for agricultural products and the sharp reduction of agricultural resources and labor force, agricultural robot technology is developing explosively on the basis of decades of technical and industrial exploration. In view of the complexity and particularity of the development of agricultural robot technology, it is of great value to summarize its development characteristics and make reasonable judgments on its development trend. In this paper, the type of agricultural robot systems was first discussed. From the classification of agricultural robot systems, the development of main types of monitoring robots, non-selective and selective working robots for crop farming, livestock and poultry farming and aquaculture were introduced in detail. Then the scientific research, core technology, and commercialization of different types of agricultural robots were summarized. It is believed that navigation in complex agricultural environments, damage-free robot-crop interaction, and agronomy-robot fusion have high scientific value and significance to promote the revolutionary advances in agricultural robot technology. The characteristics of inter-discipline between agricultural robot technology and new materials, artificial intelligence, bionics, agronomy are research focus. The fast damage-free operation, autonomous navigation for complex environments, target detection for complex backgrounds, and special design for agricultural robots are considered to be the key technology of agricultural robot development, and the development path is given. Finally, robot-crop interaction simulation, big data support, and artificial intelligence are regarded as paths to realize the breakthrough of key agricultural robot technologies. The summary and prospect of this paper are of positive significance to promote the overall development of agricultural robot technology.

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“…For example, [45] focused on strawberry harvesting and divided the cycle into perception time and harvesting time but without including in the latter the manipulator configuration time required to drop the individual fruits. Others, dedicated to collecting tomatoes, included the complete working procedure, including the time required to place the fruit into the collection box [46], [47]. For our system, the cycle picking time includes the release time because due to the weight of the aubergines, the arm must deposit grasped aubergines into a collection box before starting a new grasping motion.…”

Section: E Complete System Evaluationmentioning

confidence: 99%

Robotic Aubergine Harvesting Using Dual-Arm Manipulation

et al. 2020

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Interest in agricultural automation has increased considerably in recent decades due to benefits such as improving productivity or reducing the labor force. However, there are some current problems associated with unstructured environments make developing a robotic harvester a challenge. This article presents a dual-arm aubergine harvesting robot consisting of two robotic arms configured in an anthropomorphic manner to optimize the dual workspace. To detect and locate the aubergines automatically, we implemented an algorithm based on a support vector machine (SVM) classifier and designed a planning algorithm for scheduling efficient fruit harvesting that coordinates the two arms throughout the harvesting process. Finally, we propose a novel algorithm for dealing with occlusions using the capabilities of the dual-arm robot for coordinate work. Therefore, the main contribution of this study is the implementation and validation of a dual-arm harvesting robot with planning and control algorithms, which, depending on the locations of the fruits and the configuration of the arms, enables the following: (i) the simultaneous harvesting of two aubergines; (ii) the harvesting of a single aubergine with a single arm; or (iii) a collaborative behavior between the arms to solve occlusions. This cooperative operation mimics complex human harvesting motions such as using one arm to push leaves aside while the other arm picks the fruit. The performance of the proposed harvester is evaluated through laboratory tests that simulate the most common real-world scenarios. The results show that the robotic harvester has a success rate of 91.67% and an average cycle time of 26 s/fruit.

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Soft manipulator robot for selective tomato harvesting

Cited by 14 publications

References 7 publications

The GummiArm Project: A Replicable and Variable-Stiffness Robot Arm for Experiments on Embodied AI

The GummiArm Project: A Replicable and Variable-Stiffness Robot Arm for Experiments on Embodied AI

Development status and trend of agricultural robot technology

Robotic Aubergine Harvesting Using Dual-Arm Manipulation

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