Over the past decades, developments and scientific breakthroughs in the field of robotics have shown the replacement of wheeled robots with legged robots, which are often inspired by the biological characteristics of legged animals. Many industries and urban-based applications promote quadruped robots because of their dexterous ability to efficiently handle multiple tasks in the working environment. Motivated from the recent works in the field of quadruped robots, this research aims to develop and investigate gaits for a 2 DoF mammal-inspired quadruped robot that incorporates 4 hip and 4 knee servo motors as its locomotion element. Forward and inverse kinematic techniques are used to determine the joint angle required for the locomotion and stability calculation are presented to determine the center of mass/center of gravity of the robot. Three types of gaits such as walk, trot, and pace are developed while keeping the center of mass inside the support polygon using a closed-loop control system. To minimize errors and improve the performance of the robot due to its non-linearity, a meta-heuristic algorithm has been developed and addressed in this work. The fitness function is derived based on the Euclidean distance between the target and robot’s current position and kinematic equations are used to obtain the relation between joints and coordinates. Based on the literature, particle swarm optimization (PSO) was found to be a promising algorithm for this problem and is developed using Python’s ‘Pyswarms’ package. Experimental studies are carried out quantitatively to determine the convergence characteristics of the control algorithm and to investigate the distance traveled by the robot for different target positions and gaits. Comparison between experimental and theoretical results prove the efficiency of the proposed algorithm and stability of the robot during various gait movements.
Water scarcity is a serious issue that has to be addressed in order to face the increasing water demands. Due to this issue, agricultural crops do not receive the required amount of water. So, it is necessary to have a proper technique to determine the water requirement for a particular crop. Evapotranspiration (ET), a process which is reliant on numerous climatic conditions, quantifies the loss of water from soil and crops through evaporation and transpiration processes respectively. Reference evapotranspiration ET is a concept of estimating ET from the reference surface which resembles an in-depth surface of green grass of stable height, actively growing, fully shading the surface with sufficient water. The amount of water required for a crop is thus determined by multiplying ETo with the crop coefficient (Kc) which depends on the growth stages and duration of a crop. So, evapotranspiration is considered to be one of the successful approaches to optimize the usage of water for crops. A literature survey is carried out on the popular methods of estimating ETo and their merits, demerits are discussed in this paper. Also, the impact of various climatic factors on ETo is presented. From the survey, it is known that ETo is estimated using conventional and non-conventional methods like Penman-Monteith, Blaney-Criddle, Hargreaves, ANN and WNN, regression and fuzzy logic. Humidity, temperature, wind speed, and solar radiation are the factors that have a major impact on estimating ETo. Generally, conventional methods are tedious since it requires experimental setups and more climatic data to determine ETo which are not available in many under developing countries. Thus, in this case, non-conventional methods are found to yield better results from the survey.
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