Certain examples described herein provide a method of controlling a robotic device including a body, an end effector coupled to the body by one or more joints and a propulsion system to drive the one or more joints to control a state of the robotic device. Example methods include applying impedance control to the robotic device; determining a reference trajectory of the end effector; detecting an applied external force and/or torque acting on the robotic device causing a departure from the reference trajectory; calculating an adjustment to be applied to one or more of the one or more joints to compensate for the detected applied external force and/or torque; and using the calculated adjustment to control the one or more joints to actuate the end effector and recover the reference trajectory of the end effector.

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.

A method for controlling a mechanical system having a plurality of components interlinked by a plurality of driven joints, the method comprising: measuring torques or forces about or at the driven joints and forming a load signal representing the measured torques or forces; receiving a motion demand signal representing a desired state of the system; implementing an impedance control algorithm in dependence on the motion demand signal and the load signal to form a target signal indicating a target configuration for each of the driven joints; measuring the configuration of each of the driven joints and forming a state signal representing the measured configurations; and forming a set of drive signals for the joints by, for each joint, comparing the target configuration of that joint as indicated by the target signal to the measured configuration of that joint as indicated by the state signal.

An impedance control method as well as a controller and a robot using the same are provided. The method includes: obtaining joint motion information and joint force information in the joint space of a robotic arm and an actual interaction force acting on an end-effector, and calculating actual motion information of the end-effector in the task space based on the joint motion information; calculating a corrected desired trajectory using environment information and a desired end-effector interaction force, and calculating the impedance control torque based on the joint force information, the actual interaction force, the actual motion information, and desired end-effector information including the corrected desired trajectory and determining a compensation torque based on a nonlinear term in a constructed dynamics equation so as to perform a joint torque control on the robotic arm based on the impedance control torque and the compensation torque.

A system comprises a database; at least one hardware processor coupled with the database; and one or more software modules that, when executed by the at least one hardware processor, receive at least one of sensory data from a robot and images from a camera, identify and build models of objects in an environment, wherein the model encompasses immutable properties of identified objects including mass and geometry, and wherein the geometry is assumed not to change, estimate the state including position, orientation, and velocity, of the identified objects, determine based on the state and model, potential configurations, or pre-grasp poses, for grasping the identified objects and return multiple grasping configurations per identified object, determine an object to be picked based on a quality metric, translate the pregrasp poses into behaviors that define motor forces and torques, communicate the motor forces and torques to the robot.

A system comprising: a database configured to store a multi-body model of a robot, the robot comprising a plurality of manipulators, and a plurality of joints and plurality of actuators and actuator motors configured to move the joints, and wherein the multi-body model includes a kinematic and geometric model of each manipulator, a catalog of models for objects to be manipulated, the models comprising a current configuration and a target configuration, and a functional mapping of sensory data to configurations of the robot and the manipulators needed to manipulate the objects; at least one hardware processor coupled with the database; and one or more software modules that, when executed by the at least one hardware processor, receive sensory data from within a constrained space, identify objects in the constrained space based on the received sensory data and the catalog of models, determine a target pose for the joints and the manipulators based on the sensory data and the current and target configurations associated with the identified object, and compute joint space positions to necessary to realize the target pose.

A system comprises a database; at least one hardware processor coupled with the database; and one or more software modules that, when executed by the at least one hardware processor, receive at least one of sensory data from a robot and images from a camera, identify and build models of objects in an environment, wherein the model encompasses immutable properties of identified objects including mass and geometry, and wherein the geometry is assumed not to change, estimate the state including position, orientation, and velocity, of the identified objects, determine based on the state and model, potential configurations, or pre-grasp poses, for grasping the identified objects and return multiple grasping configurations per identified object, determine an object to be picked based on a quality metric, translate the pre-grasp poses into behaviors that define motor forces and torques, communicate the motor forces and torques to the robot in order to allow the robot to perform a complex behavior generated from the behaviors.

A robot comprising: a chopstick, configured for at least four degrees of freedom of movement, a stiff body of shape and proportions approximate to a pool cue; an electromagnetic actuator, comprising a motor, for each degree of freedom of movement coupled with the stiff body, wherein the functional mapping from each actuator's motor current to torque output along an axis of motion is stored, and used in concert with a calibrated model of the robot for effective impedance control; and a 6-axis force/torque sensor mounted inline between the actuators and each chopstick.

A method for controlling a mechanical system having a plurality of components interlinked by a plurality of driven joints, the method comprising: measuring torques or forces about or at the driven joints and forming a load signal representing the measured torques or forces; receiving a motion demand signal representing a desired state of the system; implementing an impedance control algorithm in dependence on the motion demand signal and the load signal to form a target signal indicating a target configuration for each of the driven joints; measuring the configuration of each of the driven joints and forming a state signal representing the measured configurations; and forming a set of drive signals for the joints by, for each joint, comparing the target configuration of that joint as indicated by the target signal to the measured configuration of that joint as indicated by the state signal.

A method for controlling a mechanical system having a plurality of components interlinked by a plurality of driven joints, the method comprising: measuring torques or forces about or at the driven joints and forming a load signal representing the measured torques or forces; receiving a motion demand signal representing a desired state of the system; implementing an impedance control algorithm in dependence on the motion demand signal and the load signal to form a target signal indicating a target configuration for each of the driven joints; measuring the configuration of each of the driven joints and forming a state signal representing the measured configurations; and forming a set of drive signals for the joints by, for each joint, comparing the target configuration of that joint as indicated by the target signal to the measured configuration of that joint as indicated by the state signal.