Agricultural Aid for Mango cutting (AAM)

Konam, Sandeep

doi:10.1109/icacci.2014.6968635

Cited by 13 publications

(5 citation statements)

References 7 publications

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“…With the exception of one conference presentation [33], there is no scientific literature on automation trials for mango harvesting, as revealed by a Scopus search of the string 'mango AND robotic OR mechanical AND harvest'. However, several foundation technologies are now in place.…”

Section: Mango Harvestmentioning

confidence: 99%

“…Konam [33] presented a conceptual design of a mango harvest using a quadcopter equipped with a blade as an end effector to cut the fruit stalk, with fruit falling into nets under the tree. This concept does not seem feasible because fruit will be damaged falling through the tree canopy and hitting fruit already in the net, and exuded sap will deteriorate the quality of fruit if it is left sitting on the capture net for more than a few seconds.…”

Section: Mango Harvestmentioning

confidence: 99%

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Evaluation of End Effectors for Robotic Harvesting of Mango Fruit

2023

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The task of gripping has been identified as the rate-limiting step in the development of tree-fruit harvesting systems. There is, however, no set of universally adopted ‘specifications’ with standardized measurement procedures for the characterization of gripper performance in the harvest of soft tree fruit. A set of metrics were defined for evaluation of the performance of end effectors used in soft tree-fruit harvesting based on (i) laboratory-based trials using metrics termed ‘picking area’, which was the cross-sectional area in a plane normal to the direction of approach of the gripper to the fruit in which a fruit was successfully harvested by the gripper; ‘picking volume’, which was the volume of space in which fruit was successfully harvested by the gripper; and ‘grasp force’, which was the peak force involved in removing a fruit from the grasp of a gripper; (ii) orchard-based trials using metrics termed ‘detachment success’ and ‘harvest success’, i.e., the % of harvest attempts of fruit on tree (of a given canopy architecture) that resulted in stalk breakage and return of fruit to a receiving area, respectively; and (iii) postharvest damage in terms of a score based on the percentage of fruit and severity of the damage. Evaluations were made of external (skin) damage visible 1 h after gripping and of internal (flesh) damage after ripening of the fruit. The use of the metrics was illustrated in an empirical evaluation of nine gripper designs in the harvest of mango fruit in the context of fruit weight and orientation to the gripper. A design using six flexible fingers achieved a picking area of ~150 cm2 and a picking volume of 467 cm3 in laboratory trials involving a 636 g phantom fruit as well as detachment and harvest efficiency rates of 74 and 65%, respectively, in orchard trials with no postharvest damage associated with the harvest of unripe fruit. Additional metrics are also proposed. Use of these metrics in future studies of fruit harvesting is recommended for literature–performance comparisons.

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Section: Mango Harvestmentioning

confidence: 99%

Section: Mango Harvestmentioning

confidence: 99%

Evaluation of End Effectors for Robotic Harvesting of Mango Fruit

2023

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“…Therefore, most UAS equipped with grippers and other robotic attachments will be designed for specific niche purposes. A good example comes from Konam who proposed a design that would use a robotic arm to cut ripened mangos and collect them in a net located at the base of the tree, which is work that cannot be effectively done by a ground-based system given tree heights [103]. Addressing a similar situation, Varadaramanujan and his colleagues present another UAS equipped with a robotic end-effector which can be used to pick fruits and vegetables from hard to reach areas [104].…”

Section: Gripping Toolsmentioning

confidence: 99%

Unmanned Aircraft System (UAS) Technology and Applications in Agriculture

2019

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Numerous sensors have been developed over time for precision agriculture; though, only recently have these sensors been incorporated into the new realm of unmanned aircraft systems (UAS). This UAS technology has allowed for a more integrated and optimized approach to various farming tasks such as field mapping, plant stress detection, biomass estimation, weed management, inventory counting, and chemical spraying, among others. These systems can be highly specialized depending on the particular goals of the researcher or farmer, yet many aspects of UAS are similar. All systems require an underlying platform—or unmanned aerial vehicle (UAV)—and one or more peripherals and sensing equipment such as imaging devices (RGB, multispectral, hyperspectral, near infra-red, RGB depth), gripping tools, or spraying equipment. Along with these wide-ranging peripherals and sensing equipment comes a great deal of data processing. Common tools to aid in this processing include vegetation indices, point clouds, machine learning models, and statistical methods. With any emerging technology, there are also a few considerations that need to be analyzed like legal constraints, economic trade-offs, and ease of use. This review then concludes with a discussion on the pros and cons of this technology, along with a brief outlook into future areas of research regarding UAS technology in agriculture.

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“…In these cases, the robots are usually expected to play an active role on the agricultural process. Among others [9] and [10] present two innovative solutions for automated harvesting, while in [11] the cutting of a specific tree is considered. In this scenario, the researchers of the Politecnico di Torino developed a novel wheeled UGV tailored on precision agriculture tasks and specifically design for monitoring and sampling of crops and soil [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

The Agri.q Mobile Robot: Preliminary Experimental Tests

Cavallone

Botta

Carbonari

et al. 2020

Mechanisms and Machine Science

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Precision agriculture is a management strategy aimed at enhancing the productivity, profitability, and sustainability of agricultural production from incorporation of technological advances primarily developed for other industries. Among them, robotics is playing a leading role for it allows monitoring with unprecedented punctuality the number of factors affecting the production processes. In this scenario the researchers at Politecnico di Torino developed an innovative unmanned ground vehicle expressly featured for accomplishment of monitoring tasks, with particular focus on the vine cultivation industry which is peculiarly strong in the region. The rover, named Agri.q, is an eight-wheeled mobile robot whose conceptual design has been already presented to the scientific community. This paper presents the first experimental results gathered on the prototype under different conditions of use, in order to illustrate the actual performance of Agri.q in its work environment.

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Agricultural Aid for Mango cutting (AAM)

Cited by 13 publications

References 7 publications

Evaluation of End Effectors for Robotic Harvesting of Mango Fruit

Evaluation of End Effectors for Robotic Harvesting of Mango Fruit

Unmanned Aircraft System (UAS) Technology and Applications in Agriculture

The Agri.q Mobile Robot: Preliminary Experimental Tests

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