{"response":{"award":[{"abstractText":"This Small Business Technology Transfer (STTR) Phase I project develops a robotic platform that can provide automated weed control throughout crop development stages. In recent years, weed control costs have been growing due to the rise of herbicide-resistant weeds and the increase in costs of agricultural labor. Additionally, increased demand for fruits and vegetables leaves these specialty crop farmers struggling to find options to increase productivity while keeping expenses manageable. Several companies offer automated weed control in vegetables; however, these large platforms struggle not to damage fruit in berry orchards. This project aims to develop swarms of robotic devices that can operate underneath the plant canopy to provide mechanical weed control for berries throughout the year without impacting plant growth. This technological development will enable domestic fruit production to meet the growing consumer demand and allow for less chemical use in fruit production, reducing herbicide-associated health risks to farm workers and consumers. Long term, these devices can augment weed control strategies in other crops and perform different agricultural tasks such as fungicide treatments and plant health monitoring, with the goal of automating agriculture to be more efficient and sustainable. \r\n\r\nThis Small Business Technology Transfer project aims to develop rugged, low-to-the-ground, multi-legged robots that can locomote in various agricultural fields. This technology builds off of recent works demonstrating the effectiveness of centipedes and centipede-like robots when traveling over diverse terrains. When properly coordinated, these mechanically redundant legged systems demonstrate robust locomotion in complex terrain without the need for sensory feedback. This project will leverage this platform and perform systematic robot experimentation and theoretical modeling to develop coordination schemes for various maneuvers in agricultural terrain analogues. These strategies will then be implemented on a hardened robot to reliably locomote beneath the canopy in crop fields and identify weeds using an onboard camera and computer vision techniques. This device will make use of low-cost components and principles of mobility in complex environments to deliver guaranteed locomotion in these unpredictable terrains. Eventually, swarms of these devices will be deployed on various crop fields to provide autonomous weed management throughout the growing season, decreasing the costs of production for farmers and consumers. This project will result in a robust robotic platform that can provide cheap, reliable, all-terrain locomotion and such a device can extend beyond agriculture to address other U.S. sectors such as search-and-rescue and defense.\r\n\r\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.","activeAwd":"false","agency":"NSF","awardAgencyCode":"4900","awardee":"GROUND CONTROL ROBOTICS, INC.","awardeeAddress":"720 HUNTING VIEW POINT","awardeeCity":"ATLANTA","awardeeCountryCode":"US","awardeeDistrict":"07","awardeeDistrictCode":"GA07","awardeeName":"GROUND CONTROL ROBOTICS, INC.","awardeePhone":"4046970805","awardeeStateCode":"GA","awardeeZipCode":"303282784","cfdaNumber":"47.084","coPDPI":["Flavio H Fenton flavio.fenton@physics.gatech.edu"],"date":"02/02/2024","dirAbbr":"TIP","divAbbr":"TI","estimatedTotalAmt":"275000","expDate":"09/30/2025","fundAgencyCode":"4900","fundProgramName":"STTR Phase I","fundsObligated":["FY 2024 = $275,000.00"],"fundsObligatedAmt":"275000","histAwd":"false","id":"2335553","initAmendmentDate":"02/02/2024","jrnl":[{"artTitl":"Effective Self-Righting Strategies for Elongate MultiLegged Robots","auth":"Teder, Erik and Chong, Baxi and He, Juntao and Wang, Tianyu and Iaschi, Massimiliano and Soto, Daniel and Goldman, Daniel I","authIndCode":"N","dgtlObjId":"https://doi.org/10.1109/ICRA55743.2025.11128306","jrnlYr":"2025","parPblcId":"10643104"},{"artTitl":"Probabilistic Approach to Feedback Control Enhances Multilegged Locomotion on Rugged Landscapes","auth":"He, Juntao and Chong, Baxi and Lin, Jianfeng and Xu, Zhaochen and Bagheri, Hosain and Flores, Esteban and Goldman, Daniel I","authIndCode":"N","dgtlObjId":"https://doi.org/10.1109/TRO.2025.3593133","jrnlTitl":"IEEE Transactions on Robotics","jrnlVol":"41","jrnlYr":"2025","parPblcId":"10630697"},{"artTitl":"Tactile sensing enables vertical obstacle negotiation for elongate many-legged robots","auth":"He, Juntao and Chong, Baxi and Iaschi, Massimiliano and Nienhusser, Vincent R and Ha, Sehoon and Goldman, Daniel","authIndCode":"N","jrnlYr":"2025","parPblcId":"10643108"},{"artTitl":"Addition of a Peristaltic Wave Improves Multi-Legged Locomotion Performance on Complex Terrains","auth":"Iaschi, Massimiliano and Chong, Baxi and Wang, Tianyu and Lin, Jianfeng and He, Juntao and Soto, Daniel and Xu, Zhaochen and Goldman, Daniel I","authIndCode":"N","dgtlObjId":"https://doi.org/10.1109/ICRA55743.2025.11127656","jrnlYr":"2025","parPblcId":"10643105"}],"latestAmendmentDate":"06/05/2025","managingPec":"150500","orgCodeDir":"15000000","orgCodeDiv":"15030000","orgLongName":"Directorate for Technology, Innovation, and Partnerships","orgLongName2":"Translational Impacts","orgUrl":"https://www.nsf.gov/tip","parentUeiNumber":"","pdPIName":"Daniel Soto","perfAddress":"720 HUNTING VIEW POINT","perfCity":"ATLANTA","perfCountryCode":"US","perfDistrict":"07","perfDistrictCode":"GA07","perfLocation":"GROUND CONTROL ROBOTICS, INC.","perfStateCode":"GA","perfZipCode":"303282784","pi":["Daniel Soto danielsotoz1998@gmail.com"],"piEmail":"danielsotoz1998@gmail.com","piFirstName":"Daniel","piId":"270077894","piLastName":"Soto","poEmail":"emirowsk@nsf.gov","poName":"Ela Mirowski","poPhone":"7032922936","primaryProgram":["01002425DB NSF RESEARCH & RELATED ACTIVIT"],"progEleCode":"150500","program":"ROBOTICS","progRefCode":"6840","projectOutComesReport":"
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This project, \"Weed Control via Terradynamically Robust Robots,\" advances a new approach to agricultural field maintenance and monitoring by combining fundamental discoveries in multilegged animal and robot locomotion with practical engineering to enable robots to operate reliably in real fields. This project sought to develop a robotic platform capable of navigating real-world environments through its mechanics, without the complex sensors required by other legged robots. To that end, we developed SCUTTLE (Slithering Centipede-like Undulatory Terradynamic Tactical Legged Explorer), a first-of-its-kind device that overcomes diverse terrains through its body and limb morphologies and control. With their unique shape and locomotion capabilities, swarms of SCUTTLEs are set to revolutionize specialty agriculture by providing a scalable, field-agnostic solution for organic weed control. 

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In developing SCUTTLE, Ground Control Robotics (GCR) engineers and Georgia Tech (GT) scientists explored optimal robot body shapes and strategies for sensing and control. For example, this project developed a feedback method that uses only foot-contact signals to estimate terrain roughness, without the use of cameras or visual mapping. The robot then autonomously adjusts its body shape and limb stepping to enhance locomotion across challenging terrains such as mud, rocks, and pine straw. Using this method, SCUTTLE requires only basic mechanical cues to move effectively through outdoor environments.

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Georgia Tech scientists also developed a head-mounted tactile sensing system to help the robot overcome obstacles taller than itself. Using these sensors, the robot could effectively “feel” the shape of obstacles before climbing them, modeling how largely-blind centipedes use their antennae to probe their immediate surroundings. This allowed the robot to climb objects up to five times its height, including surfaces with loose debris and changing curvature. The GT team developed control strategies to help the robot turn and right itself after flipping over, and they optimized details like leg design and body actuation method to help the robot travel through rough terrain. 

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The team at Ground Control Robotics conducted extensive outdoor testing with a series of prototypes to translate these scientific discoveries into a practical device ready for real field conditions. The GCR engineers replaced the robot’s cable-driven joints with gears better suited to heavy loads, and they introduced protective casings to increase the robot’s resistance to water, dust, and heat. They also developed a new C-shaped leg design which prevented the robot from sinking into the ground while walking and improved the robot’s ability to passively adapt to complex terrain.

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SCUTTLE’s performance exceeded that of all previous prototypes. It could traverse grass three times its height, climb 20° inclines, and navigate obstacles like wet sand and leaf litter with little impact to its speed. It could achieve a top speed of 1 mph outdoors and 1.5 mph indoors, nearly triple the top speed of past designs. These engineering efforts produced a robust system capable of reliable operation in the same cluttered environments where weeds flourish. 

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The project also explored weed control strategies. While mechanical trimmers were difficult to integrate into larger prototypes, the motion of the SCUTTLE robot passively crimped and mulched weeds in its path. This suggests that weed suppression can be achieved by leveraging the intrinsic interaction between robot legs and ground vegetation. Future work will build on this concept by integrating a lightweight roller-crimper mechanism designed specifically for agricultural weed management.

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More broadly, the results of this project have interesting scientific, engineering, and commercial implications. The field of robotics benefits from a new model of locomotion through complex environments using minimal sensing, leveraging body shape and contact interactions rather than heavy perception. The control and morphology principles which produced the SCUTTLE platform will be useful in developing field-ready devices for other challenging environments beyond the narrow scope of this project. Commercially, SCUTTLE presents a novel weed-management system that will free specialty agriculture from its dependence on chemical pesticides and expensive human labor, increasing the sustainability of farms using this technology. Further developments of this platform will support additional field management capabilities such as autonomous pest control and crop health surveillance.

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\n Last Modified: 12/12/2025
\nModified by: Daniel Soto

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