System for automatically manipulating primary packaging in secondary packaging, comprising a robot having at least one robot arm with a clamping gripper installed at a tool centre point, wherein each tool centre point has a force-torque sensor, an image recording module for recording images of at least the upper segment of the primary packaging, comprising at least two stereo cameras for recording 3-D images, and one or more processors for providing a three-dimensional point cloud, controlling the image recording module and controlling the robot on the basis of the analysis of the three-dimensional point cloud and the measurements from the force-torque sensors.

A positioning system is provided for insertions and placements with increased accuracy and precision for the placement and insertion of components into elements. The system may utilize one or more sensors to provide individual images or data for each individual insertion of components into elements. The system may use known information to compare the individual images or data to provide increased accuracy and precision for insertion of components into elements.

The present disclosure discloses an autonomous mobile grabbing method for a mechanical arm based on visual-haptic fusion under a complex illumination condition, which mainly includes approaching control over a target position and feedback control over environment information.

According to the method, under the complex illumination condition, weighted fusion is conducted on visible light and depth images of a preselected region, identification and positioning of a target object are completed based on a deep neural network, and a mobile mechanical arm is driven to continuously approach the target object; in addition, the pose of the mechanical arm is adjusted according to contact force information of a sensor module, the external environment and the target object; and meanwhile, visual information and haptic information of the target object are fused, and the optimal grabbing pose and the appropriate grabbing force of the target object are selected.

By adopting the method, the object positioning precision and the grabbing accuracy are improved, the collision damage and instability of the mechanical arm are effectively prevented, and the harmful deformation of the grabbed object is reduced.

In an embodiment, a method includes determining a given material to manipulate to achieve a goal state. The goal state can be one or more deformable or granular materials in a particular arrangement. The method further includes, for the given material, determining, a respective outcome for each of a plurality of candidate actions to manipulate the given material. The determining can be performed with a physics-based model, in one embodiment. The method further can include determining a given action of the candidate actions, where the outcome of the given action reaching the goal state is within at least one tolerance. The method further includes, based on a selected action of the given actions, generating a first motion plan for the selected action.

A holding arm for medical purposes, in particular for holding surgical mechatronic assistance systems and/or surgical instruments, includes a proximal end for attaching the holding arm to a base and a distal end for receiving a surgical mechatronic assistance system and/or surgical instrument; at least one first and one second arm segment, wherein the first arm segment is connected to a first joint and the second arm segment is connected to a second joint, wherein each joint is releasable and lockable. An operating unit is provided for bringing the holding arm into a desired pose, wherein the operating unit is adapted to release the associated joint upon contact between an operator and one of the first and second arm segments. A corresponding method is also provided.

One aspect of the present disclosure relates to a generation method for a training dataset, comprising: capturing, by one or more processors, a target object to which a marker unit recognizable under a first illumination condition is provided; and acquiring, by the one or more processors, a first image where the marker unit is recognizable and a second image obtained by capturing the target object under a second illumination condition.

The image processing device according to the invention includes: a first acquisition unit to acquire a captured image; a display control unit to display a setting screen to allow to user to set an image processing area, which is an area where predetermine image processing is performed, in the image acquired by the first acquisition unit on a display device; and a second acquisition unit configured to acquire movable range information indicating a movable range of a working device, operations of which are controlled on the basis of a result of the predetermined image processing. The display control unit controls the display of the setting screen so as to cause the user to identify a range in which the working device is not able to operate in the image, on the basis of the movable range information acquired by the second acquisition unit.

One variation of a method for automatically generating a planogram for a store includes: dispatching a robotic system to autonomously navigate within the store during a mapping routine; accessing a floor map of the floor space generated by the robotic system from map data collected during the mapping routine; identifying a shelving structure within the map of the floor space; defining a first set of waypoints along an aisle facing the shelving structure; dispatching the robotic system to navigate to and to capture optical data at the set of waypoints during an imaging routine; receiving a set of images generated from optical data recorded by the robotic system during the imaging routine; identifying products and positions of products in the set of images; and generating a planogram of the shelving segment based on products and positions of products identified in the set of images.

A mechanical tower climber system for performing operations on a cell tower includes a body; a plurality of members disposed or connected to the body and each comprising one or more robotic hands; and a wireless interface and a processing device configured to receive commands from a remote operator; climb the cell tower based on the commands; and perform one or more operations on cell site components associated with the cell tower based on the commands and manipulation of the plurality of members and associated one or more robotic hands.

The present disclosure provides a method and system by which a precise amount of a viscous fluid sealing compound can be dispensed at required locations through computer vision-based observation of the fluid deposited, its rate and amount of deposition and location; and that the dispensed fluid may be accurately shaped through robotic or other special purpose mechanism motion. The invention enables instant quality inspection of the dispensing process in terms of the locations, amounts and shapes of newly created seals.