In variants, a method for robot control can include: receiving sensor data of a scene, modeling the physical objects within the scene, determining a set of potential grasp configurations for grasping a physical object within the scene, determining a reach behavior based on the potential grasp configuration, determining a trajectory for the reach behavior, and grasping the object using the trajectory.

An insertion quality determinator is a determinator 1 that determines a quality of insertion of an insertion component 5 inserted into a hole formed in a work object. The insertion component 5 at least includes a head having the size that is impossible to be inserted into the hole, and a pillar-shaped body that extends from the head and has the thickness that is possible to be inserted into the hole. The determinator is configured to determine the quality of insertion based on positions of given parts P1-P4 of the head of the insertion component 5 inserted into the hole, in a direction perpendicular to an extending direction of the hole.

An information processing device includes: a joint detection unit that detects a joint of a person striking a pose to imitate a pose of a robot device including a joint; a human body joint angle estimation unit that estimates an angle of the joint of the person; and a mapping learning unit that learns mapping between the angle of the joint of the person and an angle of the joint of the robot device in the pose.

The present invention provides a two-degree-of-freedom rope-driven finger force feedback device. The two-degree-of-freedom rope-driven finger force feedback device includes a hand support mechanism, a thumb movement mechanism, an index finger movement mechanism, and a handle mechanism. The hand support mechanism includes a motor, a motor shaft sleeve, a sliding rail, and an inertial measurement unit (IMU) sensor. The thumb movement mechanism includes a long rotary disc, a torque sensor, an angle sensor, a thumb sleeve, a pressure sensor, two links, a thumb brace, and a thumb fixing ring. The handle mechanism includes a cylindrical handle, a pressure sensor, a flexible fixing band, and a slider. Torque is driven between the rotary disc and the motor by using a rope. The handle mechanism is movable forward and backward and is capable of automatic restoration. By means of the present invention, the problems of the high costs of a conventional finger force feedback device and the unadjustable characteristic of the conventional finger force feedback device are overcome. The device can be tightly worn and has a self-adaptive degree of freedom. Rope driving can ensure a gentle, smooth, and real feedback force. By means of the mounted sensors, information such as a hand posture, a rotation angle and a grip force of a thumb and an index finger, and a contact force of a middle finger can be transmitted in real time.

A string actuator-based exoskeleton robot includes: a driving force conversion unit including a fixed frame and a rotation pulley and mountable on a side portion of the waist of a human body; a driving unit including a driving motor providing a driving force and a pair of strings provided in double rows to have one side connected to the driving motor and the other side connected to the rotation pulley, and assisting the rotation of the rotation pulley by twisting or untwisting the pair of strings with or from each other by a rotational driving force of the driving motor to vary a length of the pair of strings; and a support unit formed to extend from the rotation pulley to at least one of a front surface or a rear surface of the femoral region of the human body to support the femoral region of the human body.

A system for trajectories imitation for robotic manipulators is provided. The system includes an interface configured to receive a plurality of task descriptions, wherein the interface is configured to communicate with a real-world robot, a memory to store computer-executable programs including a robot simulator, a training module and a transfer module, and a processor, in connection with the memory. The processor is configured to perform training using the training module, for the task descriptions on the robot simulator, to produce a plurality of source policy with subgoals for the task descriptions. The processor performs training using the training module, for the task descriptions on the real-world robot, to produce a plurality of target policy with subgoals for the task descriptions, and update the parameters of the transfer module from corresponding trajectories with the subgoals for the robot simulator and real-world robot.

An assist device includes a body mounting fixture, an actuator, an operation state detector, and a controller. The controller is configured to control drive of the actuator. The controller is configured to acquire an estimated posture of the wearer, which is estimated based on operation detection information detected by the operation state detector, when the actuator generates the assist torque. The controller is configured to determine whether or not the estimated posture is an unreasonable posture in which an excessive force is applied to a lower back portion.

A wearable device, includes a motor, a motor driver circuit, a memory, a sensor, and a processor. The memory is configured to store resistance force generation setting information indicating a difference between a reference angle and each joint angle and a corresponding relationship between respective duty ratios. The processor is configured to obtain, using the sensor, a joint angle of a user and calculate a difference between the reference angle and the obtained joint angle. The processor is configured to obtain a duty ratio corresponding to the calculated difference according to the resistance force generation setting information. The processor is further configured to provide a control signal having the obtained duty ratio to the motor driver circuit to perform control such that a control state of the motor driver circuit is switched between a first control state and a second control state.

A robot manipulator including limbs moveable via bearings controlled by actuators; sensors to capture a bearing position and a bearing torque/bearing force; a first sensor to capture a force screw W; a housing downstream of the first sensor; a second sensor to capture a user force applied to the housing and/or a user torque; a computing unit to determine, using a dynamics model of the robot manipulator and based on particular bearing torque/bearing force, the force screw W, and the user force and/or the user torque, a first force and/or a first torque to shift the limbs and a second force and/or a second torque to apply to an external object via an effector, wherein the dynamics model includes at least gravitational forces and inertial forces based on the bearing position; and a storage unit to store the first and/or the second force, and/or the first and/or the second torque.

In an embodiment, a method for handling an order includes determining a plurality of ingredients based on an order, received from a user over a network, for a location having a plurality of robots. The method further includes planning at least one trajectory for at least one robot based on the plurality of ingredients and utensils available at the location, and proximity of each ingredient and utensil to the at least one robot. Each trajectory can be configured to move one of the plurality of ingredients into a container associated with the order. In an embodiment, the method includes executing the at least one trajectory by the at least one robot to fulfill the order. In an embodiment, the method includes moving the container to a pickup area.