To generate a more appropriate path, provided is a robot path generation device including circuitry configured to: hold a track planning module learning data set, in which a plurality of pieces of path data generated based on a motion constraint condition of a robot, and evaluation value data, which corresponds to each of the plurality of pieces path data and is a measure under a predetermined evaluation criterion, are associated with each other; and generate, based on a result of a machine learning process that is based on the track planning module learning data set, a path of the robot between a set start point and a set end point, which are freely set.

Generating a robot control policy that regulates both motion control and interaction with an environment and/or includes a learned potential function and/or dissipative field. Some implementations relate to resampling temporally distributed data points to generate spatially distributed data points, and generating the control policy using the spatially distributed data points. Some implementations additionally or alternatively relate to automatically determining a potential gradient for data points, and generating the control policy using the automatically determined potential gradient. Some implementations additionally or alternatively relate to determining and assigning a prior weight to each of the data points of multiple groups, and generating the control policy using the weights. Some implementations additionally or alternatively relate to defining and using non-uniform smoothness parameters at each data point, defining and using d parameters for stiffness and/or damping at each data point, and/or obviating the need to utilize virtual data points in generating the control policy.

Generating a robot control policy that regulates both motion control and interaction with an environment and/or includes a learned potential function and/or dissipative field. Some implementations relate to resampling temporally distributed data points to generate spatially distributed data points, and generating the control policy using the spatially distributed data points. Some implementations additionally or alternatively relate to automatically determining a potential gradient for data points, and generating the control policy using the automatically determined potential gradient. Some implementations additionally or alternatively relate to determining and assigning a prior weight to each of the data points of multiple groups, and generating the control policy using the weights. Some implementations additionally or alternatively relate to defining and using non-uniform smoothness parameters at each data point, defining and using d parameters for stiffness and/or damping at each data point, and/or obviating the need to utilize virtual data points in generating the control policy.

Generating a robot control policy that regulates both motion control and interaction with an environment and/or includes a learned potential function and/or dissipative field. Some implementations relate to resampling temporally distributed data points to generate spatially distributed data points, and generating the control policy using the spatially distributed data points. Some implementations additionally or alternatively relate to automatically determining a potential gradient for data points, and generating the control policy using the automatically determined potential gradient. Some implementations additionally or alternatively relate to determining and assigning a prior weight to each of the data points of multiple groups, and generating the control policy using the weights. Some implementations additionally or alternatively relate to defining and using non-uniform smoothness parameters at each data point, defining and using d parameters for stiffness and/or damping at each data point, and/or obviating the need to utilize virtual data points in generating the control policy.

Example implementations may relate to methods and systems for determining a safe trajectory for movement of an object by a robotic system. According to these various implementations, the robotic system may determine at least first and second candidate trajectories for moving the object. For at least a first point along the first candidate trajectory, the robotic system may determine a predicted cost of dropping the object at the first point along the first candidate trajectory. And for at least a second point along the second candidate trajectory, the robotic system may determine a predicted cost of dropping the object at the second point along the second candidate trajectory. Then, based on these various determined predicted costs, the robotic system may select between the first and second candidates trajectories and may then move the object along the selected trajectory.

Dynamic control of a center of mass position is based on replacement of discrete motion of macro body (counterweighing solid or counterbalancing mechanisms) for continuous molecular flow of counterweighing liquid. Redistributing liquid counterweight between chambers attached to independently moving parts of robot allows its motion to new stable position without disruption in static stability and dynamic balance. Various embodiments include bipods/humanoids, wheeled locomotion robots and hybrid wheeled/multi-pod bio-like robotic systems; some embodiments allow reversible mutual reconfiguration between various structural arrangements. In humanoid embodiments, method allows moving on uneven terrain or ascending staircases while maintaining static stability; method also decreases the probability of fall and secures self-rising if a fall occurred. In some embodiments liquid counterweight may be transferred upon high barriers exceeding the height of robot by a few folds, such as walls of the building or ledge or steep slope in mountains, thus providing robots with capability principally not available to prior art.

New multi-computers architecture allows protection of personal computer by the combined hardware and software means reinforcing online security to the safety level not achievable using software security means alone. The disclosed system encompasses intermediate lock-computer and unidirectional internal interfaces based on novel principles providing complete security while sending information to world wide web and reliable filtering out of unwanted software while receiving information from Internet. One of the key principles underlying the present invention is physical separation of dataflow from web-connected computer to intermediate lock-computer to the main personal computer and the counter dataflow from main computer to lock-computer to web-connected computer. The interfaces in direct data flow from Internet to personal computer and in the counter dataflow may be based on different physical and system principles including novel two-dimensional image-based interface. Effectively, the disclosed methods and apparatuses provide five levels of computer defense, including four principally new levels of defense.

Generating a robot control policy that regulates both motion control and interaction with an environment and/or includes a learned potential function and/or dissipative field. Some implementations relate to resampling temporally distributed data points to generate spatially distributed data points, and generating the control policy using the spatially distributed data points. Some implementations additionally or alternatively relate to automatically determining a potential gradient for data points, and generating the control policy using the automatically determined potential gradient. Some implementations additionally or alternatively relate to determining and assigning a prior weight to each of the data points of multiple groups, and generating the control policy using the weights. Some implementations additionally or alternatively relate to defining and using non-uniform smoothness parameters at each data point, defining and using d parameters for stiffness and/or damping at each data point, and/or obviating the need to utilize virtual data points in generating the control policy.

The invention relates to a method and a device for handling of disturbances in a filling and/or closing and/or post-processing installation for the pharmaceutical industry using a manipulator (14), wherein a path along which the manipulator (14) is moved for collision-free handle of the disturbance is planned in such a way that travel paths of the manipulator (14) which influence a primary air supply (5) of primary packaging means and/or of components of the filling and/or closing and/or post-processing installation which are in contact with the primary packaging means are minimized. The invention further relates to a filling and/or closing and/or post-processing installation and a computer program for a filling and/or closing and/or post-processing installation.

Example implementations may relate to methods and systems for determining a safe trajectory for movement of an object by a robotic system. According to these various implementations, the robotic system may determine at least first and second candidate trajectories for moving the object. For at least a first point along the first candidate trajectory, the robotic system may determine a predicted cost of dropping the object at the first point along the first candidate trajectory. And for at least a second point along the second candidate trajectory, the robotic system may determine a predicted cost of dropping the object at the second point along the second candidate trajectory. Then, based on these various determined predicted costs, the robotic system may select between the first and second candidates trajectories and may then move the object along the selected trajectory.