# Mobile Robotics in Agricultural Operations:
## 2 Materials and Methods
### Definition of Planning Attributes  
Considering that the focus of this research is the planning of mobile robots in agricultural operations, in this sub-section, we primarily present the principles of mobile robots, and then we define and decompose the planning attributes encountered in an agricultural operations setting.  
Generally, mobile robot systems are recognized as \"physical agents that move and interact continuously while embedded in a dynamic environment\" [17]. Contrary to existing robotic systems which are largely fixed and heavy installations used for performing repetitive tasks, autonomous mobile robots consist a more flexible and cost-effective technology for executing sophisticated tasks without manual observation/operation. Advanced UGV and UAV systems that utilize sensors and cameras to self-localize and navigate their working environments are typically recognized as mobile robots. In an agricultural setting, UGVs are autonomous vehicles that navigate within an agri-field for soil and imagery aggregation, harvesting, spraying, weeding, etc. [18; 19]. Additionally, UAVs are used to mainly address area coverage tasks (usually referred as \"mosaicking\") with regard to the acquisition of geo-referenced aerial imagery, weed detection (high-resolution monitoring) and hydric stress determination (low-resolution monitoring).  
The interaction element within certain environments is eminent so that mobile robots \"accomplish various tasks such as visual navigation, obstacle avoidance, and landmark (and/or object) recognition\" [20]. A mobile robot typically comprises of two sub-systems (Figure 1), namely:  
1. The physical sub-system that includes the locomotion mechanism, which enables the motion-transition of the robot between two subsequent configurations, along with the sensory devices, which enable interaction with the operating environment At the physical subsystem level, the locomotion mechanism includes physical steering systems (in the case of UGVs) or piloting systems (in the case of UAVs), the necessary control mechanisms and the underpinning kinematics;
2. The computational sub-system that includes the low- and high-level control layers and refers to all algorithms and models controlling the functionality and maneuverability of the robot.  
In this work, we use the term \"locomotion planning\" to encapsulate the terms \"motion planning\", \"route planning\", and \"path planning\" that are typically used interchangeably in the literature related to automated operations enabled by robotics. A general differentiation between these terms can be based on the level of abstraction of the solution domain. The term \"motion planning\" refers to generating efficient trajectories for mobile robot systems, particularly in problems that involve kinematic constraints, dynamic constraints, object coordination, etc. Furthermore, the term \"route planning\" refers to calculating the optimal sequence (permutation) for visiting the nodes in a graph, from a topological perspective, and is equivalent to the problem of the complete traversal of a graph (in the same sense that the term is used in the family of vehicle routing optimization problems) [21; 22]. Conversely, \"path planning\" refers to the problem of determining a collision-free path, either in a topological or geometrical or trajectory sense, connecting a pre-given start and a goal point [23].  
In the following sections, locomotion planning attributes encountered in an agricultural operations setting are defined and decomposed.