Abstract: A system includes sensors, memory, and a processor. The sensors are configured to capture images of a workspace, and the memory is configured to store the images and a model of machinery located within the workspace. The processor is configured to generate a spatial representation of the workspace based on the captured images. The processor is also configured to identify non-machinery entities within the workspace and, for each of the identified entities, generate an object that specifies a spatial extent of the respective entity and a protective separation distance for the entity. Further, the processor is configured to recognize an interaction between the entities and merge the corresponding objects into a merged object specifying a protective separation distance therefor. Moreover, the processor is configured to control operation of the machinery in accordance with a safety protocol and the protective separation distance for the merged object.

Abstract: Image sensors distributed about a workcell including industrial machinery are registered using a registration object and an information tag associated therewith. The tag contains information specifying the location of the object and/or the pose of the object. This information is acquired along with images of the registration object, and the sensors are registered based at least in part on the images and the acquired information.

Abstract: A method of safely operating machinery in a workspace includes recording images of a portion of a workspace. The method also includes generating a three-dimensional (3D) representation of the portion of the workspace based on the recorded images, where the 3D representation includes one or more volumes that correspond to the portion of the workspace. Additionally, the method includes identifying one or more of the volumes as being either occupied or unoccupied. Further, the method includes mapping one or more safe zones based on the one or more identified volumes, where the safe zones correspond to one or more regions within the portion of the workspace for safe operation of machinery.

Abstract: In various embodiments, systems and methods for safely operating machinery such as industrial robots signal intrusions into and/or above computationally defined safeguarded volumes in a workspace during sensor monitoring of the workspace. Various related actions may be taken in response thereto, including restricting operation of the machinery and/or issuing safety or occlusion signals.

Abstract: A monitoring system for monitoring a portal between a three-dimensional workcell and an adjacent three-dimensional workcells each of which includes controlled machinery, the portal being traversable by humans from either of the workcells into the adjacent workcell, the monitoring system including a plurality of cameras distributed throughout at least one of the workcell or the adjacent workcell and a controller for determining a proximity of a human between the adjacent workcells, where the controller is configured to electronically signal determined expected entry of the human into the adjacent workcell, and where the controller ignores detected features at the portal unassociated with humans except following receipt of the signal indicating expected entry of the human into the adjacent workcell through the portal.

Abstract: Spatial regions potentially occupied by a robot (or other machinery) or portion thereof and a human operator during performance of all or a defined portion of a task or an application are computationally estimated. These “potential occupancy envelopes” (POEs) may be based on the states (e.g., the current and expected positions, velocities, accelerations, geometry and/or kinematics) of the robot and the human operator. Once the POEs of human operators in the workspace are established, they can be used to guide or revise motion planning for task execution.

Abstract: A method of safely operating machinery in a workspace includes recording images of a portion of a workspace. The method also includes generating a three-dimensional (3D) representation of the portion of the workspace based on the recorded images, where the 3D representation includes one or more volumes that correspond to the portion of the workspace. Additionally, the method includes identifying one or more of the volumes as being either occupied or unoccupied. Further, the method includes mapping one or more safe zones based on the one or more identified volumes, where the safe zones correspond to one or more regions within the portion of the workspace for safe operation of machinery.

Abstract: One or more computational strategies is used to reduce the complexity of handling detected point clusters appearing at a portal of a monitored workcell. If the other side of the portal is a second, adjacent workcell, the monitoring system for a first workcell predicts when a human in that workcell may pass through the portal to a second workcell and alerts the monitoring system for the second workcell. The prediction may be based on absolute proximity of a human to the portal or movement toward it. Other strategies are employed if the workcells overlap, or if the portal leads to an unmonitored space.

Abstract: In various embodiments, systems and methods for acquiring depth images utilize an architecture suited to safety-rated applications, and may include more than sensor (such as time-of-flight sensors) operating along different optical paths and a comparison module for ensuring proper sensor operation. Error metrics may be associated with pixel-level depth values for purposes of allowing safe control based on imperfectly known depths.

Abstract: An image processing system includes at least two three-dimensional sensors and a controller. Each of the sensors being for illuminating a corresponding field of view of the sensor, and generating an output array of pixelwise values indicative of distances to illuminated objects in the field of view, each sensor being configured to generate illumination at least at two different frequencies so that objects in the corresponding field of view are illuminated at the two different frequencies. The controller is communicably connected to the at least two sensors to receive pixelwise data from each sensor embodying intensity and distance information from the illuminated objects. The controller is configured to disambiguate a distance to each of the illuminated objects, resolve error in the received pixelwise data due to periodic distance ambiguity, and determine corrected pixelwise values indicative of true distance via each sensor illumination at the at least two different frequencies.

Abstract: A system includes sensors, memory, and a processor. The sensors are configured to capture images of a workspace, and the memory is configured to store the images and a model of machinery located within the workspace. The processor is configured to generate a spatial representation of the workspace based on the captured images. The processor is also configured to identify non-machinery entities within the workspace and, for each of the identified entities, generate an object that specifies a spatial extent of the respective entity and a protective separation distance for the entity. Further, the processor is configured to recognize an interaction between the entities and merge the corresponding objects into a merged object specifying a protective separation distance therefor. Moreover, the processor is configured to control operation of the machinery in accordance with a safety protocol and the protective separation distance for the merged object.

Abstract: A method of safely operating machinery in a workspace includes recording images of a portion of a workspace. The method also includes generating a three-dimensional (3D) representation of the portion of the workspace based on the recorded images, where the 3D representation includes one or more volumes that correspond to the portion of the workspace. Additionally, the method includes identifying one or more of the volumes as being either occupied or unoccupied. Further, the method includes mapping one or more safe zones based on the one or more identified volumes, where the safe zones correspond to one or more regions within the portion of the workspace for safe operation of machinery.

Abstract: An integrated system and method for monitoring a workspace, classifying regions therein, dynamically identifying safe states, and identifying and tracking workpieces utilizes semantic analysis of a robot in the workspace and identification of the workpieces with which it interacts, as well as a semantic understanding of entity properties both governing and arising from interaction with other entities for control purposes. These properties may be stored in a profile corresponding to the entity; depending on the implementation, the profile and methods associated with the entity may be stored in a data structure corresponding to the entity “class.” Volumetric regions (e.g., voxels) corresponding to each entity may be tracked and used to implement object methods and/or control methods. For example, machinery may be controlled in accordance with the attributes specified by the objects corresponding to identified entities in a monitored workspace.

Abstract: Systems and methods monitor a workspace for safety purposes using sensors distributed about the workspace. The sensors are registered with respect to each other, and this registration is monitored over time. Occluded space as well as occupied space is identified, and this mapping is frequently updated. Based on the mapping, a constrained motion plan of machinery can be generated to ensure safety.

Abstract: Spatial regions potentially occupied by a robot (or other machinery) or portion thereof and a human operator during performance of all or a defined portion of a task or an application are computationally estimated. These “potential occupancy envelopes” (POEs) may be based on the states (e.g., the current and expected positions, velocities, accelerations, geometry and/or kinematics) of the robot and the human operator. Once the POEs of human operators in the workspace are established, they can be used to guide or revise motion planning for task execution.

Abstract: In various embodiments, systems and methods for safely operating machinery such as industrial robots signal intrusions into and/or above computationally defined safeguarded volumes in a workspace during sensor monitoring of the workspace. Various related actions may be taken in response thereto, including restricting operation of the machinery and/or issuing safety or occlusion signals.

Abstract: Crosstalk mitigation among cameras in neighboring monitored workcells is achieved by computationally defining a noninterference scheme that respects the independent monitoring and operation of each workcell. The scheme may involve communication between adjacent cells to adjudicate non-interfering camera operation or system-wide mapping of interference risks and mitigation thereof. Mitigation strategies can involve time-division and/or frequency-division multiplexing.

Abstract: Spatial regions potentially occupied by a robot (or other machinery) or portion thereof and a human operator during performance of all or a defined portion of a task or an application are computationally estimated. These “potential occupancy envelopes” (POEs) may be based on the states (e.g., the current and expected positions, velocities, accelerations, geometry and/or kinematics) of the robot and the human operator. Once the POEs of human operators in the workspace are established, they can be used to guide or revise motion planning for task execution.

Abstract: Systems and methods monitor a workspace for safety purposes using sensors distributed about the workspace. The sensors are registered with respect to each other, and this registration is monitored over time. Occluded space as well as occupied space is identified, and this mapping is frequently updated. Based on the mapping, a constrained motion plan of machinery can be generated to ensure safety.

Abstract: Control systems for industrial machinery (e.g., robots) or other devices such as medical devices utilize a safety processor (SP) designed for integration into safety applications and computational components that are not necessarily safety-rated. The SP monitors performance of the non-safety computational components, including latency checks and verification of identical outputs. One or more sensors send data to the non-safety computational components for sophisticated processing and analysis that the SP cannot not perform, but the results of this processing are sent to the SP, which then generates safety-rated signals to the machinery or device being controlled by the SP. As a result, the system may qualify for a safety rating despite the ability to perform complex operations beyond the scope of safety-rated components.