An exoskeleton system includes a first exoskeleton unit configured to support a first body part, a second exoskeleton unit configured to support a second body part, and a control device. The first exoskeleton unit and the second exoskeleton unit are mechanically decoupled from each other. The control device is configured to control, based on a control model, at least one of the first exoskeleton unit and the second exoskeleton unit. The control model is based on a multibody system that models the first exoskeleton unit, the second exoskeleton unit, and at least one of the first body part and the second body part.

A method for preemptive control planning can include: optionally determining a graph that defines dependencies between behaviors; executing an execution plan for an executing behavior; generating a set of predictions with the executing behavior; propagating the set of predictions to child behaviors of the executing behavior; determining child execution plans and child predictions with the child behaviors; repeating the above for descendant behaviors of each child behavior; determining a realized world state associated with completion of the execution plan; and executing a child execution plan associated with a world state prediction matching the realized world state.

A robot includes a movable section capable of moving, a driving section configured to drive the movable section, a transmitting section located between the movable section and the driving section, a first position detecting section configured to detect a position on an input side of the transmitting section, a second position detecting section configured to detect a position on an output side of the transmitting section, and an inertial sensor provided in the movable section. The driving section is driven on the basis of a detection result of the first position detecting section, a detection result of the second position detecting section, and a detection result of the inertial sensor.

A robot controller used in a system having a machine tool and a robot, by which the robot is properly operated corresponding to an operation state of the machine tool. The robot controller has a data communicating part which obtains data representing an operation state of the machine tool at predetermined timing; a motion pattern storing part which stores a plurality of motion patterns of the robot for the machine tool; and a motion controlling part which selects a motion pattern from the stored plurality of motion patterns when an abnormality occurs in the machine tool or when an operation state of the machine tool satisfies a predefined condition, and operates the robot based on the selected motion pattern, the selected pattern being associated with an operation state of the machine tool when an abnormality occurs or when the operation state satisfies the predefined condition.

A method for preemptive control planning can include: optionally determining a graph that defines dependencies between behaviors; executing an execution plan for an executing behavior; generating a set of predictions with the executing behavior; propagating the set of predictions to child behaviors of the executing behavior; determining child execution plans and child predictions with the child behaviors; repeating the above for descendant behaviors of each child behavior; determining a realized world state associated with completion of the execution plan; and executing a child execution plan associated with a world state prediction matching the realized world state.

An exoskeleton system includes a first exoskeleton unit configured to support a first body part, a second exoskeleton unit configured to support a second body part, and a control device. The first exoskeleton unit and the second exoskeleton unit are mechanically decoupled from each other. The control device is configured to control, based on a control model, at least one of the first exoskeleton unit and the second exoskeleton unit. The control model is based on a multibody system that models the first exoskeleton unit, the second exoskeleton unit, and at least one of the first body part and the second body part.

Provided is an article retrieval system including: a sensor that measures the states of articles stored in a storage container; an article detection part for detecting the articles on the basis of the states of the articles measured by the sensor; handling part for retrieving the articles or changing the positions and/or orientations of the articles detected by the article detection part; and a controller that controls the sensor, the article detection part, and the handling part. The controller includes: a space dividing part for dividing the space in which the articles exist according to the states of the articles measured by the sensor; and a switching part for switching at least one of a method of measurement with the sensor, a method of detection with the article detection part, and a method of retrieval with the handling part in each of the spaces divided by the space dividing part.

A sensor assignment device includes a movement instruction generator for generating and submitting a movement instruction to a distinct one of a plurality of actuators to move a distinct one of a plurality of machine parts, a sensor data receiver for receiving sensor data acquired by a subset of a plurality of sensors, a degree of correlation determiner for determining sensor-specific degrees of correlation between the detected sensor data and the movement instruction, and a sensor assigner for assigning those sensors to the distinct machine part whose sensor-specific degrees of correlation exceed a predetermined threshold or a multiple-step fashion as refinement in case of insufficiently reliable map of affiliations between sensors and machine parts. The received sensor data is used to influence the movement instruction.

Motion of multiple agents with identical non-linear dynamics is controlled to change density of the agents from the initial to the final density. A first control problem is formulated for optimizing a control cost of changing density of the agents from the initial density to the final density subject to dynamics of the agents in a density space. The first control problem, which is a non-linear non-convex problem over a multi-agent control and a density of the agents, is transformed into a second control problem over the density of the agents and a product of the multi-agent control and the density of the agents. The second control problem is a non-linear convex problem that is solved to produce the control input for each section of the state space. A motion of each agent is controlled according to a control input corresponding to its section of the state space.

According to an example, a method for area occupancy information extraction may include receiving a signal from a sensor, and determining a number of occupants moving within a first area based on the signal. The method may further include determining when an occupant is moving and a direction of motion of the occupant based on the signal, and determining a most likely trajectory based on the direction of motion of the occupant. The method may also include controlling, by a processor, a service in the first area based on the determination of the number of occupants, the determination of when the occupant is moving and the direction of motion of the occupant, and/or the determination of the most likely trajectory.