Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This article presents a new hybrid motion (HM) planner, designed to allow robust indoor navigation in constrained environments of nonholonomic differential robots, such as RobChair, the brain-actuated robotic wheelchair [1] from the Institute of Systems and Robotics, University of Coimbra, Portugal. Relying on this new planning algorithm, RobChair is now able to operate in real dynamic environments and perform challenging maneuvers in narrow spaces. The HM planner integrates deliberative and reactive modules in a three-layer structure: a fast threedimensional (3-D)-global path planner, smoothing, and a new reactive local planner designated the doubledynamic window approach (D-DWA). The 3-D-global path planner consists in the A) algorithm, which defines a path composed by a sequence of (x, y) points, with an interpolation module that has the purpose of assigning an orientation to each (x, y) point. The smoothing algorithm adjusts the (x, y) points to reduce accelerations and jerk associated with the trajectory. The D-DWA is in charge of dynamically adapting the robot motion, taking into account the robot geometry (noncircular robot) and local static/dynamic obstacles, unknown from the global planner perspective. Real-time navigation is achieved because both the smoothing and the D-DWA algorithms are iteratively executed during navigation. The use of multiresolution local grid maps also contributes to the increase of computation performance. To show the effectiveness of the proposed planning algorithm, results of real navigation experiments are reported in this article. The experiments consist in steering RobChair in a real office-like scenario by different participants, using a selfpaced P300-based brain-computer interface (BCI).
['Ana Christina Brito Lopes', 'João Paulo C. Rodrigues', 'Jorge Perdigão', 'Gabriel Pires', 'Urbano Nunes']
I am writing a research paper on a idea A New Hybrid Motion Planner: Applied in a Brain-Actuated Robotic Wheelchair
[{"from": "human", "value": "I am writing a research paper on a idea A New Hybrid Motion Planner: Applied in a Brain-Actuated Robotic Wheelchair"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This article presents a new hybrid motion (HM) planner, designed to allow robust indoor navigation in constrained environments of nonholonomic differential robots, such as RobChair, the brain-actuated robotic wheelchair [1] from the Institute of Systems and Robotics, University of Coimbra, Portugal. Relying on this new planning algorithm, RobChair is now able to operate in real dynamic environments and perform challenging maneuvers in narrow spaces. The HM planner integrates deliberative and reactive modules in a three-layer structure: a fast threedimensional (3-D)-global path planner, smoothing, and a new reactive local planner designated the doubledynamic window approach (D-DWA). The 3-D-global path planner consists in the A) algorithm, which defines a path composed by a sequence of (x, y) points, with an interpolation module that has the purpose of assigning an orientation to each (x, y) point. The smoothing algorithm adjusts the (x, y) points to reduce accelerations and jerk associated with the trajectory. The D-DWA is in charge of dynamically adapting the robot motion, taking into account the robot geometry (noncircular robot) and local static/dynamic obstacles, unknown from the global planner perspective. Real-time navigation is achieved because both the smoothing and the D-DWA algorithms are iteratively executed during navigation. The use of multiresolution local grid maps also contributes to the increase of computation performance. To show the effectiveness of the proposed planning algorithm, results of real navigation experiments are reported in this article. The experiments consist in steering RobChair in a real office-like scenario by different participants, using a selfpaced P300-based brain-computer interface (BCI)."}]