This work focuses on analyzing different centralized task allocation methods for multiple quadruped systems. The goal is to assign tasks to agents by considering obstacles in the area in a way that minimizes power con...
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This work focuses on analyzing different centralized task allocation methods for multiple quadruped systems. The goal is to assign tasks to agents by considering obstacles in the area in a way that minimizes power con...
This work focuses on analyzing different centralized task allocation methods for multiple quadruped systems. The goal is to assign tasks to agents by considering obstacles in the area in a way that minimizes power consumption, completes the mission in the shortest possible time, and maximizes task completion ratio. The power consumption and cost-of-transmission for cheetah-type quadruped are analyzed, and the power consumption is extrapolated for speeds between (0.1,0.8) m/s using the results from the literature. A* path planning algorithm is utilized to consider obstacles in the area. Particle swarm optimization and genetic algorithm analyzed to show that a combination of power consumption, mission completion time, and task completion ratio can result in a more efficient and effective task allocation process compared to shortest greedy distance-based allocations. The findings can contribute to the development of more advanced and autonomous systems in various fields, leading to increased productivity, accuracy, and efficiency.
Farming is Pakistan's most basic job and plays a crucial part in the economy. A substantial portion of the land is dedicated to agriculture growing in order to meet people's demands for food, raw material expo...
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Farming is Pakistan's most basic job and plays a crucial part in the economy. A substantial portion of the land is dedicated to agriculture growing in order to meet people's demands for food, raw material expo...
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Farming is Pakistan's most basic job and plays a crucial part in the economy. A substantial portion of the land is dedicated to agriculture growing in order to meet people's demands for food, raw material export and import. As a result, it is critical to increase agricultural production, which is farmers' major competition. Crop cultivation is influenced by environmental and soil characteristics, which farmers are unaware of. A crop suggestion system is being developed to aid farmers in resolving this challenge. The construction of a system that suggests the best crop based on environmental and soil variables is done using machine learning techniques. Farmers that cultivate the recommended crop produce more and of higher quality.
A real time fault detection approach for a brushless DC motor driving a mechanical actuation system is presented. The brushless DC motor is controlled by a PWM inverter using rectangular current excitation. After an i...
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A real time fault detection approach for a brushless DC motor driving a mechanical actuation system is presented. The brushless DC motor is controlled by a PWM inverter using rectangular current excitation. After an introduction into fault detection with parameter estimation and parity equations, a mathematical model for the actuator with special emphasis on the motor itself is derived. The application of the estimation algorithm to detect electrical and mechanical parameter changes in the motor is described. In addition parity equations are used to detect sensor offsets. The fault detection scheme is implemented on a digital signal processor controlling the actuator. Finally experimental results are given.
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