Evolution Robotics

About: Evolution Robotics is a based out in . It is known for research contribution in the topics: Simultaneous localization and mapping & Robot. The organization has 48 authors who have published 68 publications receiving 4708 citations.

The vSLAM Algorithm for Robust Localization and Mapping

Abstract: This paper presents the Visual Simultaneous Localization and Mapping (vSLAMTM) algorithm, a novel algorithm for simultaneous localization and mapping (SLAM). The algorithm is vision-and odometry-based, and enables low-cost navigation in cluttered and populated environments. No initial map is required, and it satisfactorily handles dynamic changes in the environment, for example, lighting changes, moving objects and/or people. Typically, vSLAM recovers quickly from dramatic disturbances, such as “kidnapping”.

Methods and apparatus for position estimation using reflected light sources

Abstract: The invention is generally related to the estimation of position and orientation of an object with respect to a local or a global coordinate system using reflected light sources. A typical application of the method and apparatus includes estimation and tracking of the position of a mobile autonomous robot. Other applications include estimation and tracking of an object for position-aware, ubiquitous devices. Additional applications include tracking of the positions of people or pets in an indoor environment. The methods and apparatus comprise one or more optical emitters, one or more optical sensors, signal processing circuitry, and signal processing methods to determine the position and orientation of at least one of the optical sensors based at least in part on the detection of the signal of one or more emitted light sources reflected from a surface.

Control of a Quadrotor Helicopter Using Dual Camera Visual Feedback

Abstract: In this paper we propose a vision-based stabilization and output tracking control method for a model helicopter. A novel two-camera method is introduced for estimating the full six-degrees-of-freedom pose of the helicopter. One of these cameras is located on-board the helicopter, and the other camera is located on the ground. Unlike previous work, these two cameras are set to see each other. The pose estimation algorithm is compared in simulation to other methods and is shown to be less sensitive to errors on feature detection. In order to build an autonomous helicopter, two methods of control are studied: one using a series of mode-based, feedback linearizing controllers and the other using a backstepping-like control law. Various simulations demonstrate the implementation of these controllers. Finally, we present flight experiments where the proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote-controlled helicopter.

Application of localization, positioning & navigation systems for robotic enabled mobile products

Abstract: A robotic cleaner includes a cleaning assembly for cleaning a surface and a main robot body. The main robot body houses a drive system to cause movement of the robotic cleaner and a microcontroller to control the movement of the robotic cleaner. The cleaning assembly is located in front of the drive system and a width of the cleaning assembly is greater than a width of the main robot body. A robotic cleaning system includes a main robot body and a plurality of cleaning assemblies for cleaning a surface. The main robot body houses a drive system to cause movement of the robotic cleaner and a microcontroller to control the movement of the robotic cleaner. The cleaning assembly is located in front of the drive system and each of the cleaning assemblies is detachable from the main robot body and each of the cleaning assemblies has a unique cleaning function.

Robust sensor fusion for mapping and localization in a simultaneous localization and mapping (SLAM) system

Abstract: This invention is generally related to methods and apparatus that permit the measurements from a plurality of sensors to be combined or fused in a robust manner. For example, the sensors can correspond to sensors used by a mobile device, such as a robot, for localization and/or mapping. The measurements can be fused for estimation of a measurement, such as an estimation of a pose of a robot.