Experimentation on the motion of an obstacle avoiding robot
An intelligent robot can be used for applications where a human is at significant risk (like nuclear, space, military), the economics or menial nature of the application result in inefficient use of human workers (service industry, agriculture), for humanitarian uses where there is great risk (demining an area of land mines, urban search and rescue). This paper implements an experiment on one of important fields of AI Searching Algorithms, to find shortest possible solution by searching the produced tree. We will concentrate on Hill climbing algorithm, which is one of simplest searching algorithms in AI. This algorithm is one of most suitable searching methods to help expert system to make decision at every state, at every node. The experimental robot will traverse the maze by using sensors plugged on it. The robot used is E.V.3 Lego Mind storms, with native software for programming LabView. The reason we chose this robot is that it interacts quickly with sensors and can be reconstructed in many ways. This programmed robot will calculate the best possibilities to find way out of maze. The maze is made of wood, and it is adjustable, as robot should be able to leave the maze in any design.
Code (0)
등록된 구현이 없습니다.
Tasks
HumanitarianSimilar Papers 제목 키워드 기반
Simulation of optical flow and fuzzy based obstacle avoidance system for mobile robots
Honey bees use optical flow to avoid obstacles effectively. In this research work similar methodology was tested on a simulated mobile robot. Simulation framework was based on VRML and Simulink in a 3D world. Optical flo…
NavigateOptical Flow EstimationTOP-Nav: Legged Navigation Integrating Terrain, Obstacle and Proprioception Estimation
Legged navigation is typically examined within open-world, off-road, and challenging environments. In these scenarios, estimating external disturbances requires a complex synthesis of multi-modal information. This underl…
Motion PlanningDenoising Heat-inspired Diffusion with Insulators for Collision Free Motion Planning
Diffusion models have risen as a powerful tool in robotics due to their flexibility and multi-modality. While some of these methods effectively address complex problems, they often depend heavily on inference-time obstac…
Collision AvoidanceDenoisingMotion PlanningFast Robot Arm Inverse Kinematics and Path Planning Under Complex Static and Dynamic Obstacle Constraints
Described here is a simple, reliable, and quite general method for rapid computation of robot arm inverse kinematic solutions and motion path plans in the presence of complex obstructions. The method derived from the MSC…
Reactive Motion Generation With Particle-Based Perception in Dynamic Environments
Reactive motion generation in dynamic and unstructured scenarios is typically subject to essentially static perception and system dynamics. Reliably modeling dynamic obstacles and optimizing collision-free trajectories u…