Mobile robots have been widely used in automated factory applications such as raw material delivery and product storage transportation. path planning algorithms have been proposed to generate a feasible global approac...
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ISBN:
(纸本)9781665489218
Mobile robots have been widely used in automated factory applications such as raw material delivery and product storage transportation. path planning algorithms have been proposed to generate a feasible global approach. The path result must be free from obstacle regions and shortest. Previously we proposed an Improved Rapidly-Exploring Random Tree (Improved RRT*) algorithm. The algorithm consists of the pre-processing step for feasible mapping, primary processing with RRT* for path generating, and post-processing with Bacterial Mutation and Node Deletion operators. This paper aims to improve further the capability of the Improved RRT* algorithm by reducing the overall computation time. The proposed method reduces the complexity of the random map after each iteration by deleting the used nodes. In this way, the computational time could be reduced.
One of the highly essential issues in robotics is to let the mobile robot reach a predetermined location in the presence of obstacles. Many algorithms had been implemented for obstacle avoidance in an unknown environm...
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ISBN:
(纸本)9781665404693
One of the highly essential issues in robotics is to let the mobile robot reach a predetermined location in the presence of obstacles. Many algorithms had been implemented for obstacle avoidance in an unknown environment. In this research, an algorithm has been presented for the mobile robot to perform this task. This algorithm is based on the use of sensors. The robot was programmed to use various sensors such as ultrasound and infrared sensors. The proposed algorithm was implemented in many environments, which contains several obstacles. The experiments show that the mobile robot has successfully avoided the obstacles located on its path to the predetermined target.
Cílem této diplomové práce je realizovat řídicí jednotku modelu průmyslového robota ROB 2-6. Řídicí jednotka je realizována s použitím procesoru z rodiny ARM STM3...
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Cílem této diplomové práce je realizovat řídicí jednotku modelu průmyslového robota ROB 2-6. Řídicí jednotka je realizována s použitím procesoru z rodiny ARM STM32F100. Spolu s řídicí jednotkou má být realizováno HMI, které umožní nahrávání programu a obsluhu řídicí jednotky. V rámci této práce je realizován vizualizační model a algoritmus plánování dráhy v programu Matlab.
This paper presents a unique design concept, dynamic modeling, and control strategies for efficient coverage pathplanning of a glass facade cleaning robot (GFCR). The robot design has been conceptualized using mechan...
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This paper presents a unique design concept, dynamic modeling, and control strategies for efficient coverage pathplanning of a glass facade cleaning robot (GFCR). The robot design has been conceptualized using mechanisms for adhesion, motion, steering, and cleaning. The dynamic model for robot vertical glass facade cleaning is derived using Lagrangian formulation. A modified particle swarm optimization (PSO) is used to autotune the proportional, integral, and derivative (PID) parameters for the trajectory tracking simulation and it is more efficient and robust compared to the standard PSO algorithm. The path planning algorithm using hybrid PID-PSO approach is also developed for energy-efficient coverage of the robot for glass facade cleaning. The coverage algorithm illustrates the energy-performance of the GFCR for different paths viz., horizontal line sweep (HLS), vertical line sweep (VLS), spiral line sweep (SLS), and special cell diffusion (SCD) motion. Simulation reveals the robot motion for HLS path is the most energy efficient. The GFCR model with minimum energy consumption has been validated by working trials. The GFCR has potential applications for cleaning high-rise glass facade buildings and photovoltaic (PV) solar panels.
This article aims to solve the problems of high cost, low efficiency, and task delay caused by the lack of scientific scheduling strategies during the agricultural harvest season. Considering the constraints of operat...
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This article aims to solve the problems of high cost, low efficiency, and task delay caused by the lack of scientific scheduling strategies during the agricultural harvest season. Considering the constraints of operation time windows, a multimachine multiobjective cross-regional collaborative operation scheduling model is constructed with the goal of minimizing the transfer distance of agricultural machinery and nonoperational scheduling costs. A multiobjective genetic algorithm (HTSMOGA) based on a hybrid time window priority rule and a tabu search strategy is designed. The initial population is generated by utilizing time window priority rules, genes with earlier operation start times are preferentially retained, and a mixed search strategy is introduced to avoid local optimal solutions. Experiments were conducted among 24 farms in a region of Hebei Province, and the results showed that, compared with other algorithms, the HTSMOGA achieved an average reduction of 17.18 % in the transfer distance of agricultural machine operations and 19.36 % in the nonoperational waiting time. Therefore, this study provides a rational and feasible solution for the cross-regional operation scheduling of agricultural machinery cooperatives and provides theoretical support for ensuring the timely completion of harvesting tasks and the cost savings and efficiency of agricultural machinery operations.
Mobile robot navigation is a method of guiding a robot to accomplish a mission through an environment with obstacles in a good and safe manner. The main challenge of current mobile robotics is to develop intelligent n...
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ISBN:
(纸本)9781450376556
Mobile robot navigation is a method of guiding a robot to accomplish a mission through an environment with obstacles in a good and safe manner. The main challenge of current mobile robotics is to develop intelligent navigation systems, where autonomous navigation is a research focus that aims to give a machine the ability to move in an unassisted environment, without human intervention to accomplish the desired goal. The task of navigation is to give the robot the opportunity to obtain the information it needs to reason and equip it with a locomotion capacity adapted to its environment. However, it implies complex systems in the realization, where their control poses important problems not only technological but also scientific. An autonomous mobile robot is a mechanical system that must be able to make decisions to perform movements based on information about its position and the environment in which it *** problem addressed in this article is that of autonomous navigation in a dynamic environment "The objective is to study models and computer techniques allowing a mobile robot to move autonomously, that is to say without intervention in an uncertain environment and in the presence of obstacles.
The wheeled or crawled robots often suffer from big obstacles or ditches, so a hopping robot needs to fit the tough landform in the field environments. In order to jump over obstacles rapidly, a jumping sequence must ...
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The wheeled or crawled robots often suffer from big obstacles or ditches, so a hopping robot needs to fit the tough landform in the field environments. In order to jump over obstacles rapidly, a jumping sequence must be generated based on the landform information from sensors or user input. The planning method for planar mobile robots is compared with that of hopping robots. Several factors can change the planning result. Adjusting these coefficients, a heuristic searching algorithm for the jumping sequence is developed on a simplified landform. Calculational result indicates that the algorithm can achieve safety and efficient control sequences for a desired goal.
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