Abstract: Vision systems for autonomous machines and methods of using same during machine localization are provided. Exemplary systems and methods may reduce computing resources needed to perform vision-based localization by selecting the most appropriate camera from two or more cameras, and optionally selecting only a portion of the selected camera's field of view, from which to perform vision-based location correction. Other embodiments may provide camera lens coverings that maintain optical clarity while operating within debris-filled environments.

Abstract: Autonomous machine navigation techniques may generate a three-dimensional point cloud that represents at least a work region based on feature data and matching data. Pose data associated with points of the three-dimensional point cloud may be generated that represents poses of an autonomous machine. A boundary may be determined using the pose data for subsequent navigation of the autonomous machine in the work region. Non-vision-based sensor data may be used to determine a pose. The pose may be updated based on the vision-based pose data. The autonomous machine may be navigated within the boundary of the work region based on the updated pose. The three-dimensional point cloud may be generated based on data captured during a touring phase. Boundaries may be generated based on data captured during a mapping phase.

Abstract: Autonomous machine (100) navigation techniques include using simulation to configure camera (133) capture parameters. A method may include capturing image data of a scene, generating irradiance image data, determining at least one test camera capture parameter, determining a simulated scene parameter, and generating at least one updated camera capture parameter. Image data for camera capture configuration may be captured while the autonomous machine is moving. Camera (133) captures parameters may be used to capture images while the autonomous machine (100) is slowed or stopped, particularly in lowlight conditions.

Abstract: Autonomous machine navigation techniques may generate a three-dimensional point cloud that represents at least a work region based on feature data and matching data. Pose data associated with points of the three-dimensional point cloud may be generated that represents poses of an autonomous machine. A boundary may be determined using the pose data for subsequent navigation of the autonomous machine in the work region. Non-vision-based sensor data may be used to determine a pose. The pose may be updated based on the vision-based pose data. The autonomous machine may be navigated within the boundary of the work region based on the updated pose. The three-dimensional point cloud may be generated based on data captured during a touring phase. Boundaries may be generated based on data captured during a mapping phase.

Abstract: Autonomous machine navigation techniques may generate a three-dimensional point cloud that represents at least a work region based on feature data and matching data. Pose data associated with points of the three-dimensional point cloud may be generated that represents poses of an autonomous machine. A boundary may be determined using the pose data for subsequent navigation of the autonomous machine in the work region. Non-vision-based sensor data may be used to determine a pose. The pose may be updated based on the vision-based pose data. The autonomous machine may be navigated within the boundary of the work region based on the updated pose. The three-dimensional point cloud may be generated based on data captured during a touring phase. Boundaries may be generated based on data captured during a mapping phase.

Abstract: Embodiments of the present invention include multi-sensory stereo vision sensors suitable for use in robotics, navigation, machine vision, manufacturing, and other applications. In some cases, a sensor includes a stereo camera that produces image data for use in generating disparity maps to determine the positions of objects in the scene and/or the position of the sensor itself. The stereo sensor may include image sensors that are fastened to a unitary frame to prevent undesired drift and a thermal pad that wicks heat away from a processor. The processor may provide an efficient means to directly compute stereo disparity maps onboard the sensor. A sensor can also include a laser rangefinder that provides range data suitable for calibrating the stereo camera and for improving its accuracy in certain environments. In some cases, the laser is coupled to a spindle, which in turn is driven by a geartrain through a slipping clutch.

Abstract: The present invention encompasses software that brings together computer vision and machine learning algorithms that can evaluate and sort plants into desired categories. While one embodiment of the present invention is directed toward strawberry plants, the software engine described is not specifically designed for strawberry plants but can be used for many different types of plants that require sophisticated quality sorting. The present invention is a sequence of software operations that can be applied to various crops (or other objects besides plants) in a re-usable fashion.

Abstract: Embodiments of the present invention include multi-sensory stereo vision sensors suitable for use in robotics, navigation, machine vision, manufacturing, and other applications. In some cases, a sensor includes a stereo camera that produces image data for use in generating disparity maps to determine the positions of objects in the scene and/or the position of the sensor itself. The stereo sensor may include image sensors that are fastened to a unitary frame to prevent undesired drift and a thermal pad that wicks heat away from a processor. The processor may provide an efficient means to directly compute stereo disparity maps onboard the sensor. A sensor can also include a laser rangefinder that provides range data suitable for calibrating the stereo camera and for improving its accuracy in certain environments. In some cases, the laser is coupled to a spindle, which in turn is driven by a geartrain through a slipping clutch.

Abstract: The present invention encompasses software that brings together computer vision and machine learning algorithms that can evaluate and sort plants into desired categories. While one embodiment of the present invention is directed toward strawberry plants, the software engine described is not specifically designed for strawberry plants but can be used for many different types of plants that require sophisticated quality sorting. The present invention is a sequence of software operations that can be applied to various crops (or other objects besides plants) in a re-usable fashion.

Abstract: A robotic device for use in surgery includes a first surgical instrument having a proximal end, a distal end, and a shaft extending therebetween, the distal end of the first instrument and adjacent shaft being insertable distally into a first incision; a first manipulator movably supporting the first instrument; a plurality of motorized drives coupled to the manipulator; an input device having an input movable in two degrees of freedom; and a computer coupling the input device to the motorized drives so that the motorized drives effect a motion of the first surgical instrument in response to movement of the input, a center of the motion located along the shaft at the incision when the first instrument is used during surgery.

Abstract: A robotic device for use in surgery includes a first surgical instrument having a proximal end, a distal end, and a shaft extending therebetween, the distal end of the first instrument and adjacent shaft being insertable distally into a first incision; a first manipulator movably supporting the first instrument; a plurality of motorized drives coupled to the manipulator; an input device having an input movable in two degrees of freedom; and a computer coupling the input device to the motorized drives so that the motorized drives effect a motion of the first surgical instrument in response to movement of the input, a center of the motion located along the shaft at the incision when the first instrument is used during surgery.

Abstract: Image processing is used to determine information about the position of a designated object, particularly where the object is difficult to view or locate. In particular, use in endoscopic surgery can determine positional information about an anatomical feature within a patient's body. The positional information is then used to position or reposition a surgical instrument in relation to the designated object. An instrument placed in relation to the designated object is capable of sending information about the object to a computer. Image processing generates images and determines positional information, which can be used as input to robotic devices or rendered to a human user.

Abstract: The invention comprises an instrument which is placed in relation to the designated object and which is capable of sending information about the object to a computer. Image processing methods are used to generated images of the object and determine positional information about it. This information can be used as input to robotic devices or can be rendered, in various ways (video graphics, speech synthesis), to a human user. Various input apparatus are attached to the transmitting or other used instruments to provide control inputs to the computer.