A method for moving along a predetermined path with a robot in an at least a partially automated manner includes determining a deployment position on a current path section of the predetermined path for which a distance parameter satisfies a predetermined condition, and moving to the deployment position with the robot. In one aspect, the robot may be moved to the deployment position if a deployment condition is satisfied. The distance parameter may be determined on the basis of a distance of a current position of the robot relative to the current path section. The predetermined condition may be that the distance parameter has a value that is less than or equal to the values of the distance parameter of all positions in a partial area of the current path section, which is in particular complementary to the deployment position.

A method in accordance with the invention for modification of a robot path which has a plurality of path points comprises the following steps of specifying a modification region which has at least two path points of the robot path, specifying a modification of a reference point of the modification region, and automated modification of the modification region, in particular of path points of the modification region, on the basis of the specified modification.

One variation of a method for controlling a robotic arm includes: moving the robotic arm through a trajectory; at a first time in which the robotic arm occupies a first position along the trajectory, measuring a first capacitance of a first sense circuit comprising a first electrode extending over a first arm segment of the robotic arm; at a second time in which the robotic arm occupies a second position along the trajectory, measuring a second capacitance of the first sense circuit; calculating a first rate of change in capacitance of the first sense circuit based on a difference between the first capacitance and the second capacitance; in response to the first rate of change in capacitance of the first sense circuit exceeding a threshold rate of change, issuing a proximity alarm; and reducing a speed of the robotic arm moving through the trajectory in response to the proximity alarm.

A path generation device includes maximum displacement axis calculation means that calculates a maximum displacement axis among multiple axes, where the maximum displacement axis has a highest ratio of a displacement distance relative to a maximum speed in a motion from a motion start point to a motion end point; initial passing point calculation means that generates passing points to be used when the multiple axes move in synchronization with one another; interference area extraction means that extracts a section including a passing point on which interference with a surrounding object will occur, among multiple passing points generated by the initial passing point calculation means; and non-maximum displacement axis modification means that generates a passing point that leads to avoidance of interference, by modifying a position of a non-maximum displacement axis, which is, among the multiple axes, an axis other than the maximum displacement axis calculated.

The present invention relates to a trajectory generating method for moving a Robot Arm in the fastest and smoothest path by avoiding obstructions and jerky movements in the shortest possible time to predetermined endpoints, by implementing a planning, sequence and trajectory path manager to plan the movements ahead of time and concurrently creating a database of trajectory paths that is subsequently used for storing and retrieving of repetitive movements of the Robot arm, resulting in time saving and smooth movements. In a dynamically changing operating environment, endpoints are calculated through the implementation of an intelligence module that captures a three-dimensional image of the processing area and predicts a 3D pose, which in turn is translated to positional coordinates for the Robot to utilise, to move to the target endpoint. The planning manager working in sync with the intelligence module and sequence manager enables a very favourable environment to seamlessly and efficiently move objects smoothly at controlled speeds, mimicking human movement.

A processing system is disclosed for providing processing of objects that include 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 a destination bin, 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.

Various embodiments of the technology described herein generally relate to systems and methods for trajectory optimization with machine learning techniques. More specifically, certain embodiments relate to using neural networks to quickly predict optimized robotic arm trajectories in a variety of scenarios. Systems and methods described herein use deep neural networks to quickly predict optimized robotic arm trajectories according to certain constraints. Optimization, in accordance with some embodiments of the present technology, may include optimizing trajectory geometry and dynamics while satisfying a number of constraints, including staying collision-free and minimizing the time it takes to complete the task.

A method for controlling a robot. The method includes determining, for each robotic pose of a plurality of predetermined robot trajectories, a respective embedding in an embedding space having the structure of a hyperbolic manifold by searching an optimum of an objective function which incites, for each of the predetermined robot trajectories, the embeddings of the robotic poses of the predetermined robot trajectory to follow pre-defined dynamics of the embedding space, determining, for a starting pose from which the robot is to be controlled, a start embedding in the embedding space (, and, for a desired end pose, an end embedding in the embedding space and a geodesic between the start embedding and the end embedding according to a pullback metric of the embedding space and controlling the robot according to a sequence of robotic poses given by the determined geodesic.

A dynamic target tracking method for a robot having multiple joints includes: obtaining a motion state of a tracked dynamic target in real time; performing motion prediction according to the motion state at a current moment to obtain a predicted position of the dynamic target; performing lag compensation on the predicted position to obtain a compensated predicted position; performing on-line trajectory planning according to the compensated predicted position to obtain planning quantities of multi-step joint motion states at multiple future moments, and determining a multi-step optimization trajectory according to the planning quantities and a multi-step optimization objective function; and controlling the joints of the robot to according to the multi-step optimization trajectory.

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.