# Autonomous Robotics for Identification and Management of Invasive Aquatic Plant Species
## 1 Introduction  
### Impact and Treatment of Aquatic Weeds  
While native aquatic plants are essential components of aquatic ecosystems, non-native invasive species can expand rapidly throughout water bodies and cause severe economic and ecological impacts (Figure 1) [1; 2]. Adverse economic impacts include: impairing recreational activities (fishing, swimming, and boating); flooding caused by reduced drainage; hindering boat navigation; blocking water intakes for hydroelectric turbines, drinking water, and irrigation; and reducing the potability of fresh water due to foul taste and odor [1; 3; 4; 5]. Indirect economic effects include reduced property values and reduced revenue from impacted businesses [2; 6]. Aquatic flora consume oxygen at night; thus, excessive weed growth can deprive fish and other aquatic animals of this vital resource, leading to their death. Other ecological effects include overpopulation of small fish, which find shelter in the plants, and the creation of breeding habitats for some mosquito species [3]. Of the many invasive aquatic plant species, _Hydrilla verticillata_, commonly known by its genus _Hydrilla_, likely causes themost economic damage in the United States [1]. In Florida alone, state and federal entities spend millions of dollars annually towards _Hydrilla_ management ($14.5 million in 1997 [1] and $66 million total from 2008 to 2015 [7]). The economic impact on a single water body is significant; a detailed study on a single Florida lake estimated potential _Hydrilla_-related losses of $40 million per year (property values, agricultural support, flood control, recreation, etc.) [6].  
Given these adverse impacts, management of invasive aquatic vegetation is of utmost concern. While mechanical control (plucking or raking the plants) is the most direct approach, it can be time-consuming and costly (estimated cost of $1000 per acre in 1996) [8; 9]. Biological control methods (e.g., fish which consume large quantities of aquatic weeds) are routinely employed but can be counter-productive. One example is the grass carp, which can consume and control vegetation [9]; however, their body waste compromises water quality, killing sensitive plants and animal species, and fertilizing additional weed growth [3; 10]. Biological approaches also introduce the risk of invasive animal species [11]. Seven species of carp native to Asia, introduced to control invasive plant species, have recently spread up the Mississippi River system and have crowded out native fish populations. While not without its drawbacks, chemical control (the application of herbicides) is considered the most attractive aquatic weed management method in terms of minimizing cost, time, and collateral damage [5]. Efficient chemical-based vegetation control in aquatic bodies requires proper identification and quantification of the extent to which vegetation is present, both for optimal chemical selection and treatment strategies [3; 4]. The approach of manually identifying weed-infested regions within a water body and applying herbicides at the target location(s) is labor intensive, time-consuming, and involves risk of herbicide exposure to personnel [12]. Spraying herbicide throughout the water body leads to much higher usage, resulting in economic loss, longer decomposition times, and subsequent environmental hazards. Two unmanned watercraft, the TORMADA (Lake Restoration Inc., Rogers, MN) and WATER STRIDER (Yamaha Motor Company, Iwata, Shizuoka, Japan) are commercially available for herbicide dispersal in water bodies. These boats offer remote control by a human operator but have limited tank capacity (3.8 and 8.0 L for TORMADA and WATER STRIDER, respectively) and lack autonomous navigation and weed identification functionality. [PERSON] outlined the design, fabrication, and testing of an autonomous boat for monitoring algae blooms in Lake Geneva and has included a summary of multiple autonomous watercraft developed by other authors [13].