Experimental study demonstrates autonomous roadside navigation and targeted weed removal using a compact vision-based mobile robot, highlighting scalable automated road maintenance.
In this study, we propose a compact autonomous roadside weeding robot, R4 (Ritsumeikan Road-weed Removal Robot), aimed at reducing human labor in road infrastructure maintenance. Conventional weeding robots are often designed for agricultural or horticultural applications and are unsuitable for operation in roadside environments where drivable areas are limited. The proposed robot has a compact structure with a width of 603 mm, depth of 512 mm, and height of 368 mm, minimizing the risk of contact with vehicles. A low-cost autonomous navigation system was developed using a single RGB camera to determine a path along the roadside independent of lighting and pavement conditions. Furthermore, a lightweight weed detection algorithm was developed to deploy the weeding mechanism only when weeds are present, enabling safe operation without human intervention. The experiments conducted in both indoor and outdoor environments demonstrated the stability of the autonomous navigation system, efficiency of the weed detection algorithm, and practical applicability of the proposed robot.
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Matsushita et al. (2026) studied this question.
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