Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Map building is an important issue for all the applications in mobile robotics in which the environment is unknown and, in general, in order to have a robot exhibit a fully autonomous behavior. A major problem in map building is due to the imprecision of sensor measures. ,  propose a technique, called elastic correction, for correcting the dead-reckoning errors made during the exploration of an environment by a robot capable of identifying landmarks. Knowledge being acquired is modeled by a relational graph whose vertices and arcs represent, respectively, landmarks and routes. Elastic correction is based on an analogy beten the graph modeling the environment and a mechanical structure: the map is regarded as a truss where each route is an elastic bar and each landmark a node. Errors are corrected as a result of the deformations induced from the forces arising within the structure as inconsistent measures are taken. The elasticity parameters characterizing the structure are used to model the uncertainty on odometry. The paper presents results from simulations showing the effectiveness of the method for reducing the overall metric error and proving its robustness with reference to topological errors and to unpredictable sensor errors.
['Matteo Golfarelli', 'Dario Maio', 'Stefano Rizzi']
I am writing a research paper on a idea Correction of dead-reckoning errors in map building for mobile robots
[{"from": "human", "value": "I am writing a research paper on a idea Correction of dead-reckoning errors in map building for mobile robots"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Map building is an important issue for all the applications in mobile robotics in which the environment is unknown and, in general, in order to have a robot exhibit a fully autonomous behavior. A major problem in map building is due to the imprecision of sensor measures. ,  propose a technique, called elastic correction, for correcting the dead-reckoning errors made during the exploration of an environment by a robot capable of identifying landmarks. Knowledge being acquired is modeled by a relational graph whose vertices and arcs represent, respectively, landmarks and routes. Elastic correction is based on an analogy beten the graph modeling the environment and a mechanical structure: the map is regarded as a truss where each route is an elastic bar and each landmark a node. Errors are corrected as a result of the deformations induced from the forces arising within the structure as inconsistent measures are taken. The elasticity parameters characterizing the structure are used to model the uncertainty on odometry. The paper presents results from simulations showing the effectiveness of the method for reducing the overall metric error and proving its robustness with reference to topological errors and to unpredictable sensor errors."}]