A robotic arm assembly includes a robotic arm, a base, and a utility member, the robotic arm extending between a root end attached to the base and a distal end including the utility member. A method for controlling the robotic arm assembly includes: determining a position of the base, the root end, or both relative to the environment; determining a task position and orientation for the utility member within the environment; determining a three-dimensional constraint of the environment; and determining a path for the robotic arm through the environment based on each of the position of the base, the root end, or both relative to the environment, the task position and orientation for the utility member within the environment, and the three-dimensional constraint of the environment.

In a trajectory generation apparatus, position coordinates of an obstacle existing in a motion space of a robot arm is acquired. A hand position at a second time, which is a time next to a first time, is estimated by using a learning result of machine learning, based on the position coordinates of the obstacle, a subject joint state of the robot arm at the first time, and a target joint state of the robot arm. A non-interfering joint state of the robot arm at which the obstacle does not interfere with the robot arm at the second time is searched for by using the hand position as a restriction.

The present disclosure provides a robotic arm control method as well as an apparatus and a terminal device using the same. The method includes: obtaining a current joint angle of each of M joints of the robotic arm; obtaining a reference included angle based on the current joint angle of each of the M joints of the robotic arm; determining an expected included angle corresponding to the robotic arm within a target angle range based on the reference included angle and the preset included angle related evaluation function; and controlling the robotic arm based on the target joint angles of the M joints.

The present teaching relates to a method and system for path planning. A target is tracked via one or more sensors. Information of a desired pose of an end-effector with respect to the target and a current pose of the end-effector is obtained. Also, a minimum distance permitted between an arm including the end-effector and each of at least one obstacle identified between the current pose of the end-effector and the target is obtained. A weighting factor previously learned is retrieved and a cost based on a cost function is computed in accordance with a weighted smallest distance between the arm including the end-effector and the at least one obstacle, wherein the smallest distance is weighted by the weighting factor. A trajectory is computed from the current pose to the desired pose by minimizing the cost function.

A robotic system comprising: a robot having a base and an arm extending from the base to an attachment for an instrument, the arm comprising n joints, where n>1, whereby the configuration of the arm can be altered, the arm having a plurality of configurations for a given relationship between the base and the attachment for the instrument, the robot comprising a driver for each joint configured to drive the joint to move and a joint sensor for each joint for sensing a state of the joint; and a control unit configured to: obtain a desired position of the attachment for the instrument; for each of k joints where k<n, obtain a sensed joint state; compare the obtained k sensed joint states to a set of constraint criteria, the set of constraint criteria being indicative of the arm moving from a first configuration towards a second configuration, where movement of the arm is more constrained in the second configuration than in the first configuration; where the obtained k sensed joint states match the set of constraint criteria, determine a magnitude of an adjustment signal configured to slow, halt or reverse movement of the arm towards the second configuration; using the desired position of the attachment for the instrument and the obtained k sensed joint states, determine a direction of the adjustment signal; for each of the n joints, obtain a sensed joint state; using the desired position of the attachment for the instrument, the obtained n sensed joint states and the adjustment signal, determine a set of control signals for controlling the drivers; and drive the joints using the set of control signals.

A method for controlling a robot includes detecting current positions of joints of the robot and actuating the joints using drives of the robot based on the detected current joint positions such that at least one drive supports a manual guidance-induced movement of the joint actuated by the drive if a distance between the detected or target joint position and a specified first boundary has a first value. The drive supports the manual guidance-induced movement to a lesser degree if the distance has a second value which is lower than the first value. Additionally, the manual guidance-induced movement is oriented towards the first boundary.

A robotic arm assembly includes a robotic arm, a base, and a utility member, the robotic arm extending between a root end attached to the base and a distal end including the utility member. A method for controlling the robotic arm assembly includes: determining a position of the base, the root end, or both relative to the environment; determining a task position and orientation for the utility member within the environment; determining a three-dimensional constraint of the environment; and determining a path for the robotic arm through the environment based on each of the position of the base, the root end, or both relative to the environment, the task position and orientation for the utility member within the environment, and the three-dimensional constraint of the environment.

A method for controlling the motion of one or more collaborative robots is described, the collaborative robots being mounted on a fixed or movable base, equipped with one or more terminal members, and with a motion controller, the method including the following iterative steps: determining the position coordinates of the robots, and the position coordinates of one or more human operators collaborating with the robot; determining a set of productivity indices associated with relative directions of motion of the terminal member of the robot, the productivity indices being indicative of the speed at which the robot can move in each of the directions without having to slow down or stop because of the presence of the operator; supplying the controller of the robot with the data of the set of productivity indices associated with the relative directions of motion of the terminal member of the robot, so that the controller can determine the directions of motion of the terminal member of the robot based on the higher values of the productivity index.

Devices, systems, and methods for avoiding collisions between a manipulator arm and an outer patient surface by moving the manipulator within a null-space. In response to a determination that distance between an avoidance geometry and obstacle surface, corresponding to a manipulator-to-patient distance is less than desired, the system calculates movement of one or more joints or links of the manipulator within a null-space of the Jacobian to increase this distance. The joints are driven according to the reconfiguration command and calculated movement so as to maintain a desired state of the end effector. In one aspect, the joints are also driven according to a calculated end effector displacing movement within a null-perpendicular-space of the Jacobian to effect a desired movement of the end effector or remote center while concurrently avoiding arm-to-patient collisions by moving the joints within the null-space.

Method and system for formally analyzing motion planning of a robotic arm based on conformal geometric algebra. The method includes determining specific structural and motion planning parameters of a robot, establishing a corresponding geometric model for the basic components and motion planning constraints of the robot based on a conformal geometric algebra theory, the established geometric model being described in a higher-order logic language, performing formal modeling for a motion process of the robot based on the established geometric model to obtain a logic model of the geometric relations involved in the motion process of the robot, obtaining a motion logic relationship corresponding to a constraint or attribute of a motion process to be verified of the robot, and verifying whether the motion logic relationship is correct. The method and system are used for analysis to improve the accuracy of the verification and reduce the complexity of the computations.