Agri-Cost-Maps - Integration of Environmental Constraints into Navigation Systems for Agricultural Robots

Ponnambalam, Vignesh Raja; Fentanes, Jaime Pulido; Cielniak, Grzegorz; Gjevestad, Jon Glenn Omholt; From, Pål Johan

doi:10.1109/iccar49639.2020.9108030

Cited by 9 publications

(6 citation statements)

References 13 publications

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“…Similarly, Raja et.al. [22] developed a customized costmap used for smart navigation avoidance during an agricultural task that avoids stepping on healthy crops.…”

Section: Related Workmentioning

confidence: 99%

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Towards Safe Robotic Agricultural Applications: Safe Navigation System Design for a Robotic Grass-Mowing Application through the Risk Management Method

2023

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Safe navigation is a key objective for autonomous applications, particularly those involving mobile tasks, to avoid dangerous situations and prevent harm to humans. However, the integration of a risk management process is not yet mandatory in robotics development. Ensuring safety using mobile robots is critical for many real-world applications, especially those in which contact with the robot could result in fatal consequences, such as agricultural environments where a mobile device with an industrial cutter is used for grass-mowing. In this paper, we propose an explicit integration of a risk management process into the design of the software for an autonomous grass mower, with the aim of enhancing safety. Our approach is tested and validated in simulated scenarios that assess the effectiveness of different custom safety functionalities in terms of collision prevention, execution time, and the number of required human interventions.

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“…Similarly, Raja et.al. [22] developed a customized costmap used for smart navigation avoidance during an agricultural task that avoids stepping on healthy crops.…”

Section: Related Workmentioning

confidence: 99%

“…Crop-following is a set of global and local planners with parameter values set for such behaviours. A customized agricultural task costmap based on [22] constrains the planners to avoid undesired behaviours. Finally, row changing defines an MPC for the differential drive to turn in tighter curves than an Ackerman drive.…”

Section: Execution Modulementioning

confidence: 99%

Towards Safe Robotic Agricultural Applications: Safe Navigation System Design for a Robotic Grass-Mowing Application through the Risk Management Method

2023

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“…During the last 5 years a few authors have demonstrated that hardware and software designs that address the perceptual difficulties outdoors (Kusumam et al, 2017;Ponnambalam et al, 2020;Binch et al, 2020) can lead to systems capable of long-term deployments in agricultural scenarios (Pretto et al, 2020). A recent report provides an overview on fruit harvesting robots, which have come to the market over the last 5 years (Bogue, 2020), and concludes that the time of mobile manipulation in agriculture is near.…”

Section: Related Workmentioning

confidence: 99%

Towards new frontiers in mobile manipulation: Team CTU-UPenn-NYU at MBZIRC 2020

Štibinger¹,

Broughton²,

Majer³

et al. 2022

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In this paper we present an autonomous robotic system for picking, transporting, and precisely placing magnetically graspable objects. Such a system would be especially beneficial for construction tasks where human presence is not possible, e.g. due to chemical or radioactive pollution. The system comprises of two primary components – a wheeled, mobile platform and a manipulator arm. Both are interconnected through an onboard computer and utilize various onboard sensors for estimating the state of the robot and its surroundings. By using efficient processing algorithms, data from the onboard sensors can be used in a feedback loop during all critical operational sections, resulting in a robust system capable of operating on uneven terrain and in environments without access to satellite navigation. System functionality has been proven in Challenge II of the MBZIRC 2020 competition. The Challenge required a ground robot to build an L-shaped structure of colored bricks laid in a predefined pattern. Such a mission incorporates several demanding subchallenges, spanning multiple branches of computer science, cybernetics, and robotics. Moreover, all the subchallenges had to be performed flawlessly in rapid succession, in order to complete the Challenge successfully. The extreme difficulty of the task was highlighted in the MBZIRC 2020 finals, where our system was among the only two competitors (out of 32) that managed to complete the task in autonomous mode.

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“…The results show a significant lack of reliability, if the robots are deployed outside of laboratory conditions. However, the challenges of reliable robotic perception in the real-world outdoor environment are slowly being overcome, as new sensors and processing methods are developed [27]- [29]. Novel approaches also allow for longterm deployment of agricultural robotic systems [30].…”

Section: A Related Workmentioning

confidence: 99%

Mobile Manipulator for Autonomous Localization, Grasping and Precise Placement of Construction Material in a Semi-structured Environment

Stibinger¹,

Broughton²,

Majer³

et al. 2020

Preprint

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Mobile manipulators have the potential to revolutionize modern agriculture, logistics and manufacturing. In this work, we present the design of a ground-based mobile manipulator for automated structure assembly. The proposed system is capable of autonomous localization, grasping, transportation and deployment of construction material in a semi-structured environment. Special effort was put into making the system invariant to lighting changes, and not reliant on external positioning systems. Therefore, the presented system is self-contained and capable of operating in outdoor and indoor conditions alike. Finally, we present means to extend the perceptive radius of the vehicle by using it in cooperation with an autonomous drone, which provides aerial reconnaissance. Performance of the proposed system has been evaluated in a series of experiments conducted in real-world conditions.

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Agri-Cost-Maps - Integration of Environmental Constraints into Navigation Systems for Agricultural Robots

Cited by 9 publications

References 13 publications

Towards Safe Robotic Agricultural Applications: Safe Navigation System Design for a Robotic Grass-Mowing Application through the Risk Management Method

Towards Safe Robotic Agricultural Applications: Safe Navigation System Design for a Robotic Grass-Mowing Application through the Risk Management Method

Towards new frontiers in mobile manipulation: Team CTU-UPenn-NYU at MBZIRC 2020

Mobile Manipulator for Autonomous Localization, Grasping and Precise Placement of Construction Material in a Semi-structured Environment

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