Multi-Robot Information Gathering for Precision Agriculture: Current State, Scope, and Challenges

Dutta, Ayan; Roy, Sambuddha; Kreidl, O. Patrick; Bölöni, Ladislau

doi:10.1109/access.2021.3130900

Cited by 33 publications

(22 citation statements)

References 95 publications

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“…With a pre-installed configuration, the fundamental agricultural practises like sprinkler irrigation and drip irrigation are also carried out automatically [12]. The Arduino Uno R3 microcontroller utilised in this circuit configuration is based on the Android operating system [13].…”

Section: Monitoring Soil Nutrientsmentioning

confidence: 99%

A novel design for carrying out automated agricultural tasks using an agriculturally developed robot

Manjunath¹

2023

IJETMS

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This paper gives the design and development of a precision farming robot. Since a long time ago, agriculture has been a significant part of the Indian economy. 18% of India's gross domestic product is produced by the agriculture sector (GDP). A better answer for precision agriculture is provided by robotics and the internet of things. Selective harvesting is necessary when picking fruits or vegetables like tomatoes and apples. In traditional farming, each fruit is hand-picked by a worker, requiring a huge amount of labour to carry out selective farming. We suggest a robot that helps farmers with a variety of labor-intensive chores, such as selective crop harvesting and qualitative segregation, while also simultaneously providing data on crop health, soil nutritional status, and crop shelf-life detection. An android application is used to analyse, process, and send the obtained data to the farmer. Later, the weight, colour, and health of the particular crop are checked to grade its quality. The fruit is subsequently moved into the designated container after being graded. Spoiled or overripe fruits and vegetables would be plucked and dropped so as not to interfere with the plant's growth. A harvesting arm on the proposed robot would reach the fruit or vegetable and pick it from the plant or tree. The fruit would then be transferred to the appropriate container. With the aid of the app, the user would be able to give the device a certain task based on his requirements. Crop health monitoring, segregation, and selective harvesting all require image processing using a camera. Additionally, using image processing, illnesses are found. The image segmentation and pre-processing are being done by us. The guided, supervised, and advanced machine learning technique k-nearest neighbours (KNN) is used to build solutions for both classification and regression issues. This gives the farmer useful information that is essential for choosing the correct insecticides, herbicides, and fertilisers for higher yield. Every nation's primary issue and developing topic is agriculture automation. The need for food is rising rapidly as the world's population is growing at an extremely rapid rate. Farmers must apply toxic pesticides more frequently since their traditional methods are insufficient to meet the growing demand. This damages the soil. This has a significant impact on agricultural practises, and as a result, the land remains unproductive and desolate. You can employ a variety of automation techniques, including IOT, wireless communications, machine learning, artificial intelligence, and deep learning. The work given here is a mini-project that is taken up as a part of the curriculum completed by lectronics and communication engineering students in the second year of the electronics & communication engineering department at Dayananda Sagar College of Engineering in Bangalore.

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Section: Monitoring Soil Nutrientsmentioning

confidence: 99%

A novel design for carrying out automated agricultural tasks using an agriculturally developed robot

Manjunath¹

2023

IJETMS

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“…Denote S * and S ls as the optimal solution and solution obtained by CLS (Alg. 1) for (7), by using g(•) as the oracle. We have the following worst-case performance guarantee for the objective:…”

Section: Centralized Local Search (Cls)mentioning

confidence: 99%

“…Remark 4. Having the constant O term in (7) does not change the optimization in Problem 1, but ensures that the oracle used by CLS (Alg. 1) is non-negative so that the ratio (1 + α N 4 ) correctly reflects the sufficient improvement condition.…”

Section: Centralized Local Search (Cls)mentioning

confidence: 99%

“…Developments in sensing and mobility have enabled effective utilization of robot systems in diverse applications, such as autonomous mapping [1]- [4], agriculture [5]- [7], search and rescue [8]- [11], and environmental monitoring [12]- [16]. These tasks require spatiotemporal information collection which can be achieved more efficiently and accurately by larger robot teams, rather than individual robots.…”

Section: Introductionmentioning

confidence: 99%

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Non-Monotone Energy-Aware Information Gathering for Heterogeneous Robot Teams

Cai

Schlotfeldt

Khosoussi

et al. 2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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This paper considers the problem of safely coordinating a team of sensor-equipped robots to reduce uncertainty about a dynamical process, where the objective trades off information gain and energy cost. Optimizing this trade-off is desirable, but leads to a non-monotone objective function in the set of robot trajectories. Therefore, common multi-robot planners based on coordinate descent lose their performance guarantees. Furthermore, methods that handle non-monotonicity lose their performance guarantees when subject to inter-robot collision avoidance constraints. As it is desirable to retain both the performance guarantee and safety guarantee, this work proposes a hierarchical approach with a distributed planner that uses local search with a worst-case performance guarantees and a decentralized controller based on control barrier functions that ensures safety and encourages timely arrival at sensing locations. Via extensive simulations, hardware-in-the-loop tests and hardware experiments, we demonstrate that the proposed approach achieves a better trade-off between sensing and energy cost than coordinate descent based algorithms.

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“…Multi-robot exploration of an unknown space is a fundamental task for mobile robot systems. A wide range of applications for mobile robot exploration using a group of robots can be mentioned, including autonomous transportation [ 1 ], industry [ 2 , 3 ], healthcare [ 4 ], rescue [ 5 , 6 , 7 ], and agriculture [ 8 , 9 , 10 , 11 ]. A robot must be able to navigate in a known or unknown environment [ 12 ] without human assistance.…”

Section: Introductionmentioning

confidence: 99%

Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration

Romeh

Mirjalili

2023

Sensors

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Multi-robot exploration means constructing a finite map using a group of robots in an obstacle chaotic space. Uncertainties are reduced by distributing search tasks to robots and computing the best action in real time. Many previous methods are based on deterministic or meta-heuristic algorithms, but limited work has combined both techniques to consolidate both classes’ benefits and alleviate their drawbacks. This paper proposes a new hybrid method based on deterministic coordinated multi-robot exploration (CME) and the meta-heuristic salp swarm algorithm (SSA) to perform the search of a space. The precedence of adjacent cells around a robot is determined by deterministic CME using cost and utility. Then, the optimization process of the search space, improving the overall solution, is achieved utilizing the SSA. Three performance measures are considered to evaluate the performance of the proposed method: run time, percentage of the explored area, and the number of times when a method failed to continue a complete run. Experimental results compared four different methods, CME-GWO, CME-GWOSSA, CME-SCA, and CME, over seven maps with extra complexity varying from simple to complex. The results demonstrate how the proposed CME-SSA can outperform the four other methods. Moreover, the simulation results demonstrate that the proposed CME-SSA effectively distributes the robots over the search space to run successfully and obtain the highest exploration rate in less time.

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Multi-Robot Information Gathering for Precision Agriculture: Current State, Scope, and Challenges

Cited by 33 publications

References 95 publications

A novel design for carrying out automated agricultural tasks using an agriculturally developed robot

A novel design for carrying out automated agricultural tasks using an agriculturally developed robot

Non-Monotone Energy-Aware Information Gathering for Heterogeneous Robot Teams

Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration

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