Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing robot plan online adjustment. A method includes receiving an initial plan for performing a particular task with a robot having a sensor. The initial plan defines an initial path having a plurality of waypoints. Each waypoint is associated with a target position and a target velocity. The method includes generating an alternative path from the initial path. Generating an alternative path includes generating a plurality of alternative paths including performing respective modifications to one or more waypoints in the initial plan, evaluating each alternative path according to a simulated total time duration required for the robot to traverse the alternative path, and selecting an alternative path having a total time duration that is less than a total time duration of the initial plan.

A method for generating a trajectory for a load transported by a hoisting appliance spanning a hoisting area. The method includes providing a 3-dimensional model of the hoisting area with located obstacles within the hoisting area, providing load parameters including load length, height, width and weight. Generating a trajectory for navigating through the hoisting area using the model of the hoisting area and taking in account located obstacles, load parameters; and load movement parameters including a maximum attainable speed of the hoist appliance with the load, wherein the generated trajectory includes a starting point, a target point and a number of consecutive line segments connecting the starting point and the target point. And optimizing the trajectory for speed by maximizing the length of at least one line segment in a main direction of travel in order to travel at a maximum attainable speed of the hoisting appliance with the load in the main direction of travel.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robot plan online adjustment. A method includes receiving an initial plan for performing a particular task with a robot having a sensor. The initial plan defines an initial path having a plurality of waypoints and a footprint space for performing the particular task. The method includes receiving a sensor input from the sensor, and determining from the sensor input that the initial plan requires modification to complete the particular task. The method includes evaluating a plurality of alternative paths, including rejecting one or more alternative paths having any alternative waypoints that are outside the footprint space defined by the initial plan. The method includes selecting an alternative path having alternative waypoints that are all within the footprint space defined by the initial plan. The method includes following, by the robot, the alternative path.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing robot plan online adjustment. A method includes receiving an initial plan for performing a particular task with a robot having a sensor. The initial plan defines an initial path having a plurality of waypoints. Each waypoint is associated with a target position and a target velocity. The method includes generating an alternative path from the initial path. Generating an alternative path includes generating a plurality of alternative paths including performing respective modifications to one or more waypoints in the initial plan, evaluating each alternative path according to a simulated total time duration required for the robot to traverse the alternative path, and selecting an alternative path having a total time duration that is less than a total time duration of the initial plan.

The invention relates to a method for generating a trajectory for a load transported by a hoisting appliance spanning a hoisting area. The method includes providing a 3-dimensional model of the hoisting area with located obstacles within the hoisting area, providing load parameters including load length, height, width and weight. Generating a trajectory for navigating through the hoisting area using the model of the hoisting area and taking in account located obstacles, load parameters; and load movement parameters including a maximum attainable speed of the hoist appliance with the load, wherein the generated trajectory includes a starting point, a target point and a number of consecutive line segments connecting the starting point and the target point. And optimizing the trajectory for speed by maximizing the length of at least one line segment in a main direction of travel in order to travel at a maximum attainable speed of the hoisting appliance with the load in the main direction of travel.

A control device for a machine, with at least one axis, is configured to accept first parameters and to render a first general technological problem as a first specific technological problem. The control device is configured to determine once in advance, for a sequence of values of a position or a temporal derivation of the position of the axis of the machine, a number of variables assigned to the respective value, to solve the first specific technological problem in an optimum way. The control device is configured to store the assigned variables in a memory and, after the storage of the assigned variables, is configured to accept a first execution command. Based upon the first execution command, it is configured to output the sequence of values to the axis and during output, is configured to activate the machine in accordance with the number of variables assigned to the respective value.

Provided are a planning and control method for a legged robot, an apparatus, a robot, and a storage medium. The method includes: determining, based on the movement state and the swing parameter of each leg at the next moment, a foot-end reference state of each leg, and planning, based on a foot-end dynamic model and a discrete collision model, an impact-aware swing leg trajectory for a leg that starts to swing at the next moment; and performing, based on the movement state, the reference state sequence, and the foot-end reference state, whole-body control on the legged robot, and performing, based on a whole-body dynamic model and the discrete collision model, impact-aware whole-body control for a leg that is a supporting leg in planning but does not touch the ground.