Method and system for brace designing. The method comprises the following steps: S1) fixing a subject requiring a brace; S2) acquiring skeletal image information of the subject; S3) determining an adjustment solution for implementing an adjustment with respect to the subject and a target state that is to be achieved ultimately; S4) adjusting the subject to alter the skeletal structure of the subject; S5) acquiring adjusted skeletal image information of the subject; S6) determining whether the skeleton of the subject has been adjusted to the target state; if yes, then terminating adjustment and entering step S7; if not, then returning to step S4; S7) acquiring the body surface three-dimensional shape of the subject having achieved the target state and recording information of the force applied by an adjusting head to the subject for use in manufacturing a corresponding brace; thus allowing the highly efficient designing of a brace.

This disclosure relates generally to a method and system that provides personalized neuro motor rehabilitation therapy using a musculoskeletal arm model. The arm model is personalized using anthropometric measures and further adapted to operate using an optimized set of muscle actuators considering associated redundancy. The method generates trajectories associated with reach motion profiles for each motion task utilizing joint kinematics and inverse dynamics by integrating forward dynamics and muscle synergy concepts to select the optimized set of muscle actuators. The generated trajectories are further ranked based on muscle synergy, minimum energy consumption and optimized trajectory to select rehabilitation therapy best suited for effective recovery. Conventional methods that work with neural dynamics in deriving muscle synergy are dependent on single tasks, leaving synergy variation with task variability unexplored. The present disclosure provides understanding of work space, task variability and synergy paradigm to derive conclusive control actions for aiding rehabilitation effectively.

A biomimetics based robot is disclosed. The robot may include filament driven and fluid pumped elastomer based artificial muscles coordinated for slow twitch/fast twitch contraction and movement of the robot by one or more microcontrollers. A process may provide physics based simulation for movement of a robot in a virtual setting. Embodiments include artificial skin and sensor systems in the artificial muscles and artificial skin whose feedback is used to control the muscles and movement of the robot.

Described is a system for co-adaptation of robot control to human biomechanics. During operation, the system receives joint angle and joint velocity of a human and co-robot and generates estimated internal states of the human. A task space motion plan is then generated for the co-robot based on a specified cooperative task and estimated internal states and joint angle and joint velocity of the human. Joint torque commands are then generated based on the task space motion plan and joint angle and joint velocity of the human and co-robot. Motion of the co-robot is then controlled, such as causing the co-robot to actuate one or more actuators to move based on the joint torque commands.

A learning unit of a learning system generates the following learning model. That is, this learning model is a model that inputs, for each predetermined period, rehabilitation data about rehabilitation performed by a trainee using a rehabilitation support system, and predicts a change in a setting parameter. The setting parameter is a setting parameter in the rehabilitation support system that is used when the trainee performs the rehabilitation. The rehabilitation data includes at least index data, trainee data, and training data, the index data indicating at least one of a symptom, a physical ability, and a degree of recovery of the trainee, the trainee data indicating a feature of the trainee, the training data including the setting parameter. Further, the learning unit generates a learning model by using, as teacher data, data obtained in a period until the index data reaches a predetermined target level.

A calculation device for calculating an appropriate stowage pattern of articles, and a robot controller including the calculation device. The calculation device has: a model generating section configured to generate first physical models of the articles based on dimensions of respective types of the articles, and generate a second physical model of a containing region in which the articles are stacked, based on a dimension of the containing region; a locating section configured to locate the first models in the second model, in descending order of priority predetermined with respect to the types of the articles; and a physical calculating section configured to add vibration or a shock to the second model each time when the first models is located in the second model, and calculate a change in a position and/or orientation of the first model in the second model due to the vibration or the shock.

Higher demands for adaptable, scalable and automated human resources, capabilities and services, such as human well-being, safety and security, universal health care system and educational institutions, are growing in our societies, leading the way to the creation of a new artificially-intelligent support system that can facilitate the lives of the many. The current invention aims to help resolve such issues by offering a relief system that uses a new robotic specie, called Human-Robots (HRs) and that are intended to improve the quality of our lives in terms of education, health-care, well-being, safety and security. The new specie may autonomously work and move in close proximities with and among HBs and within their natural environments, to share their workloads and tasks and is especially tuned to their well-beings and of their surroundings. The robotic specie is reliant on a standard reconfigurable system and platform that can take multiple shapes, be modular, incremental, scalable, mobile, intelligent, connected, social, and possibly fully-autonomous. The new HR society will form the new race of autonomous personal and public service providers and take part in our society as a new specie.

Method and system for brace designing. The method comprises the following steps: S1) fixing a subject requiring a brace; S2) acquiring skeletal image information of the subject; S3) determining an adjustment solution for implementing an adjustment with respect to the subject and a target state that is to be achieved ultimately; S4) adjusting the subject to alter the skeletal structure of the subject; S5) acquiring adjusted skeletal image information of the subject; S6) determining whether the skeleton of the subject has been adjusted to the target state; if yes, then terminating adjustment and entering step S7; if not, then returning to step S4; S7) acquiring the body surface three-dimensional shape of the subject having achieved the target state and recording information of the force applied by an adjusting head to the subject for use in manufacturing a corresponding brace; thus allowing the highly efficient designing of a brace.

A calculation device for calculating an appropriate stowage pattern of articles, and a robot controller including the calculation device. The calculation device has: a model generating section configured to generate first physical models of the articles based on dimensions of respective types of the articles, and generate a second physical model of a containing region in which the articles are stacked, based on a dimension of the containing region; a locating section configured to locate the first models in the second model, in descending order of priority predetermined with respect to the types of the articles; and a physical calculating section configured to add vibration or a shock to the second model each time when the first models is located in the second model, and calculate a change in a position and/or orientation of the first model in the second model due to the vibration or the shock.

A robot simulator includes a generating unit, a display unit, a display control unit, and a simulation instructing unit. The generating unit generates a virtual image that includes a virtual robot obtained by imaging an actual robot having at least one axis and an operation handle capable of operating three-dimensional coordinate axes having a predetermined control point of the virtual robot as the origin. The display control unit displays on the display unit the generated virtual image. The simulation instructing unit, when an operator's operation for the operation handle is received, acquires at least one of a displacement amount of the control point and a rotation amount of the three-dimensional coordinate axes attributable to the operator's operation, and instructs the generating unit to regenerate the virtual image in which a posture of the virtual robot is changed in accordance with the displacement amount or the rotation amount thus acquired.