首页|Researchers from Manipal Academy of Higher Education Report Findings in Androids (Multi-objective Route Outlining and Collision Avoidance of Multiple Humanoid R obots In a Cluttered Environment)
Researchers from Manipal Academy of Higher Education Report Findings in Androids (Multi-objective Route Outlining and Collision Avoidance of Multiple Humanoid R obots In a Cluttered Environment)
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Current study results on Robotics - An droids have been published. According to news reporting originating from Karnata ka, India, by NewsRx correspondents, research stated, "In robotics, navigating a humanoid robot through a cluttered environment is challenging. The present stud y aims to enhance the footstep and determine optimal paths regarding the robot's route length." Our news editors obtained a quote from the research from the Manipal Academy of Higher Education, "The objective function for navigation of multiple humanoid ro bots is presented to optimize the route length and travel time. A hybrid techniq ue using a probabilistic roadmap (PRM) and firefly algorithm (FA) is presented f or humanoid robot navigation in a cluttered environment with static and dynamic obstacles. Sensory information, such as barrier range in the left, right, and fr ont directions, is fed into the PRM framework that allows the humanoid robot to walk steadily with an initial steering angle. It finds the shortest path using t he Bellman-Ford algorithm. The FA technique is used for efficient guidance and f ootstep modification in a cluttered environment to find a smooth and optimized p ath. To avoid static obstacles, the suggested hybrid technique provides optimum steering angles and ensures the minimum route length by taking the output of PRM as its input. A 3D simulator and a real-world environment have been used for si mulation and experiment in a cluttered environment utilizing the developed model and standalone methods. The humanoid robot achieves the target in all scenarios , but the FA-tuned PRM technique is advantageous to this purpose, as shown by th e convergence curve, route length, and travel duration. Multiple humanoid robot navigation has an additional self-collision issue, which is eliminated by employ ing a dining philosopher controller as the base technique. In addition, the prop osed controller is evaluated in contrast to the existing technique."
KarnatakaIndiaAsiaAndroidsEmergi ng TechnologiesMachine LearningNano-robotRobotRoboticsManipal Academy of Higher Education
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