Remote Sensing to Minimize Energy Consumption of Six-axis Robot Arm Using Particle Swarm Optimization and Artificial Neural Network to Control Changes in Real Time

Abstract

We propose a new method for the analysis and design of a robotic system that minimizes the energy consumption of a six-axis robot arm by controlling the velocity and acceleration of each arm of the robot to achieve the specified trajectory of the robot determined from a lean manufacturing method. A dynamic model of the PUMA 560 robot has been simulated on MATLAB, while the Robotics Toolbox and particle swarm optimization (PSO) are utilized to search for optimal paths and the optimal velocity and acceleration of the robot arms. The optimal velocity and acceleration are described as those giving minimum overall energy consumption constrained by a specified cycle time of the entire robotic system. Typically, the picking and placing of materials are carried out by humans, causing a variation in production rate, whereas our system using a robot arm ensures a stable production rate. Moreover, the optimal results obtained from PSO are adopted to train an artificial neural network (ANN) to extend the design system from discrete optimal values to a continuous and near-optimal value. In other words, the ANN is used to obtain an approximate optimal value between those obtained from PSO to make the system applicable to a real-world system. As shown by the simulation results, this method reduces the energy consumption of 12.3% from the initial energy and reduces the time for optimization by 99.8% compared with that for the PSO technique.

Inundation Analysis Method for Urban Mountainous Areas Based on Soil Conservation Service Curve Number (SCS-CN) Model Using Remote Sensing Data

“…The river network is affected by topographic partitioning and fractured with no coherent river system flowing through Mingxi. Because the pre-precipitation soil moisture content and loss of vegetation root systems can affect runoff, the AMC (17) is divided into three levels according to the antecedent precipitation index (API). These include levels A (drought), B (normal), and C (moist).…”

“…Remote sensing technology offers a range of advantages for data acquisition (e.g., collection of all-weather, all-directional, multiplatform, multispectral, multialtitude, multiangle, multitemporal, and multispatial data) that can accurately reflect land-use and morphological changes. (3,4,(17)(18)(19) To quantitatively analyze rainfall-runoff characteristics and obtain more accurate flood inundation area estimates, we propose a new method of flood inundation analysis based in the SCS-CN model using remote sensing data. We test the validity of our method in the region of Mingxi, China.…”

Machining Path Optimization of 3C Locking Robots Using Adaptive Ant Colony Optimization

“…A three-dimensional Cartesian coordinate system [21][22][23] establishes the working environment of the 3C locking SCARA robot. In the three-dimensional space, the lower-left corner of the laptop is used as the coordinate origin, the horizontal direction of the origin is the X-axis, the vertical direction of the origin is the Y-axis, and the thickness direction of the laptop is the Z-axis.…”

Adsorption control of a pipeline robot based on improved PSO algorithm

“…In PSO algorithm, every positioning particle is a potential solution to a question. Every particle has its own position and speed and produces random solution at the phase of initialization [18][19][20]. Speed stands for the rapidness and slowness of the motion and position indicates the direction of the motion.…”