In this system, regarding an conveyance object placed on a rotary table, based on positions temporarily set previously as a taking position of the disk-shaped conveyance object in a storing container and a reference position of the rotary table, information of the taking position of the conveyance object in the storing container and of the reference position of the rotary table is acquired based on information of the deviation of the conveyance object placed on the rotary table with respect to the reference position of the rotary table acquired by a sensor portion so as to teach a conveying operation of the conveyance object from the storing container to the rotary table by the robot based on the acquired position information.

A processing system is disclosed for providing processing of homogenous and non-homogenous objects in both structured and cluttered environments. The processing system includes a programmable motion device including an end effector, a perception system for recognizing any of the identity, location, and orientation of an object presented in a plurality of objects at an input location, a grasp acquisition system for acquiring the object using the end effector to permit the object to be moved from the plurality of objects to one of a plurality of destination bins, and a motion planning system for determining a changing portion of a trajectory path of the end effector from the object to a base location proximate to the input location, and determining an unchanging portion of a trajectory path of the end effector from the base location to a destination bin location proximate to a destination bin, wherein the unchanging portion of the trajectory path is chosen to provide a path from the base location to the destination bin location that is consistent with paths taken by other objects.

Methods, apparatus, systems, and computer-readable media are provided for determining one or more spatial constraints associated with an object to be acted upon by a robot; determining a plurality of candidate physical arrangements of the object that satisfy the one or more spatial constraints; calculating, for one or more of the plurality of candidate physical arrangements of the object, a candidate physical arrangement cost that would be incurred as a result of the robot acting upon the object in the candidate physical arrangement; and selecting, from the plurality of candidate physical arrangements, a candidate physical arrangement associated with a candidate physical arrangement cost that satisfies a criterion.

A system for robot and human collaboration. The system comprises: a multi-axis robot; one or more torque sensors, each torque sensor being configured to measure a torque about a respective axis of the multi-axis robot; and a controller configured to: receive one or more torque measurements taken by the one or more torque sensors; compare the one or more torque measurements or a function of the one or more torque measurements to a threshold value; and control the multi-axis robot based on the comparison.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for rule execution in an online robotics system. One of the systems includes an execution engine subsystem and an execution memory subsystem. The execution engine receives rules having types and subtypes that represent a particular entity in an operating environment of a robot, provides subscription requests to the execution memory subsystem, and receives events emitted by the execution memory subsystem. The an execution memory receives subscription requests from the execution engine subsystem, receives new observations, converts the new observations into fact updates, performs pattern matching with the fact updates against the patterns of the subscription requests, and emits events to the execution engine subsystem for patterns that have been matched by the fact updates.

A complicated motion program is taught, in a simple manner, to a lead-through teachable robot. Provided is a teaching apparatus for a robot, the teaching apparatus being provided with: a movement-instruction input portion that is attached to the robot and with which a movement instruction for the robot is input; and a command input portion with which it is possible to set at least one of a movement-trajectory defining command, a standby command, a speed-changing command, and a work-condition changing command at an arbitrary position on a movement pathway of the robot in a direction that corresponds to the movement instruction input via the movement-instruction input portion.

A rigid-flexible coupling high-accuracy galvo scanning motor comprises: a stator, a rotor rotating relative to the stator, bearing seats and at least two groups of encoders. The rigid-flexible coupling bearings are installed on the rotating shaft of the rotor; each of the rigid-flexible coupling bearings comprises: a rigid bearing and a flexible hinge ring which is elastically deformable, and the flexible hinge ring is fixed in an inner ring of the rigid bearing; the at least two groups of encoders comprise: a first group of encoders and a second group of encoders; the first group of encoders is used to measure a rotation angle of the rotating shaft; and the second group of encoders is used to measure a rotation angle of the inner ring of the rigid bearing. A friction dead zone is avoided through the elastic deformation of the flexible hinge ring, thereby reducing a disturbance bandwidth.

The present disclosure relates to a computer-implemented method for customizing an automated product manufacturing process. It further relates to a robotic manufacturing system for manufacturing a product based on a fabrication model generated by means of the aforementioned computer-implemented method. One embodiment relates to a computer-implemented method for customizing a parametric design and manufacturing process of a physical product, the method comprising the steps of: obtaining a configurable parametric 3D product model representing a template of the physical product; customizing by a user the parametric 3D product model to provide a product instance describing the desired geometry of the physical product; automatically updating a fabrication model based on the parametric 3D product model; and optionally submitting the fabrication model to a manufacturing machine for fabricating the physical product or a mould for the physical product.

A method for generating intermediate waypoints for a navigation system of a robot includes receiving a navigation route. The navigation route includes a series of high-level waypoints that begin at a starting location and end at a destination location and is based on high-level navigation data. The high-level navigation data is representative of locations of static obstacles in an area the robot is to navigate. The method also includes receiving image data of an environment about the robot from an image sensor and generating at least one intermediate waypoint based on the image data. The method also includes adding the at least one intermediate waypoint to the series of high-level waypoints of the navigation route and navigating the robot from the starting location along the series of high-level waypoints and the at least one intermediate waypoint toward the destination location.

Methods and systems are provided for high-speed constrained motion planning. In one embodiment, a method includes computing, with a neural network trained on trajectories generated by a non-convex optimizer, a trajectory from one or more initial states of an autonomous system to one or more final states of the autonomous system, updating, with the non-convex optimizer, the trajectory according to kinematic limits and dynamic limits of the autonomous system to obtain a final trajectory, and automatically controlling the autonomous system from an initial state of the one or more initial states to a final state of the one or more final states according to the final trajectory. In this way, efficient and smooth trajectories can be rapidly computed for effective real-time control while accounting for obstacles and physical constraints of an autonomous system.