Abstract: A system and method is disclosed for predicting a fall of a robot having at least two legs. A learned representation, such as a decision list, generated by a supervised learning algorithm is received. This learned representation may have been generated based on trajectories of a simulated robot when various forces are applied to the simulated robot. The learned representation takes as inputs a plurality of features of the robot and outputs a classification indicating whether the current state of the robot is balanced or falling. A plurality of features of the current state of the robot, such as the height of the center of mass of the robot, are determined based on current values of a joint angle or joint velocity of the robot. The current state of the robot is classified as being either balanced or falling by evaluating the learned representation with the plurality of features of the current state of the robot.

Abstract: A controller and control method assists a driver with backing up of a vehicle with an attached trailer. The vehicle has a front axle with steerable front wheels controlled by the driver and a rear axle with non-steerable rear wheels. The trailer has a front axle with non-steerable front wheels and a rear axle with steerable rear wheels controlled by a trailer steering controller. The controller receives an operator-controlled vehicle steering angle and a measured hitch angle. The controller determines a trailer steering angle based on the operator-controller vehicle steering angle and the measured hitch angle. The controller continuously controls the trailer (e.g., via a steering angle of the rear wheels) to maintain a trajectory with substantially no lateral slippage.

Abstract: A system and method is disclosed for controlling a robot having at least two legs, the robot falling down from an upright posture and the robot located near a plurality of surrounding objects. A plurality of predicted fall directions of the robot are determined, where each predicted fall direction is associated with a foot placement strategy, such as taking a step, for avoiding the surrounding objects. The degree to which each predicted fall direction avoids the surrounding objects is determined. A best strategy is selected from the various foot placement strategies based on the degree to which the associated fall direction avoids the surrounding objects. The robot is controlled to implement this best strategy.

Abstract: A system and method is disclosed for controlling a robot that is falling down from an upright posture. Inertia shaping is performed on the robot to avoid an object during the fall. A desired overall toppling angular velocity of the robot is determined. The direction of this velocity is based on the direction from the center of pressure of the robot to the object. A desired composite rigid body inertia of the robot is determined based on the desired overall toppling angular velocity. A desired joint velocity of the robot is determined based on the desired composite rigid body inertia. The desired joint velocity is also determined based on a composite rigid body inertia Jacobian of the robot. An actuator at a joint of the robot is then controlled to implement the desired joint velocity.

Abstract: A momentum-based balance controller controls a humanoid robot to maintain balance. The balance controller derives desired rates of change of linear and angular momentum from desired motion of the robot. The balance controller then determines desired center of pressure (CoP) and desired ground reaction force (GRF) to achieve the desired rates of change of linear and angular momentum. The balance controller determines admissible CoP, GRF, and rates of change of linear and angular momentum that are optimally close to the desired value while still allowing the robot to maintain balance. The balance controller controls the robot to maintain balance based on a human motion model such that the robot's motions are human-like. Beneficially, the robot can maintain balance even when subjected to external perturbations, or when it encounters non-level and/or non-stationary ground.

Abstract: A system and method is disclosed for controlling a robot having at least two legs that is falling down from an upright posture. An allowable stepping zone where the robot is able to step while falling is determined. The allowable stepping zone may be determined based on leg Jacobians of the robot and maximum joint velocities of the robot. A stepping location within the allowable stepping zone for avoiding an object is determined. The determined stepping location maximizes an avoidance angle comprising an angle formed by the object to be avoided, a center of pressure of the robot upon stepping to the stepping location, and a reference point of the robot upon stepping to the stepping location. The reference point, which may be a capture point of the robot, indicates the direction of fall of the robot. The robot is controlled to take a step toward the stepping location.

Abstract: A robot controller controls a robot to maintain balance in response to an external disturbance (e.g., a push) on level or non-level ground. The robot controller determines a predicted stepping location for the robot such that the robot will be able to maintain a balanced upright position if it steps to that location. As long as the stepping location predicted stepping location remains within a predefined region (e.g., within the area under the robot's feet), the robot will maintain balance in response to the push via postural changes without taking a step. If the predicted stepping location moves outside the predefined region, the robot will take a step to the predicted location in order to maintain its balance.

Abstract: A humanoid robot fall controller controls motion of a robot to minimize damage when it determines that a fall is unavoidable. The robot controller detects a state of the robot during the fall and determines a desired rotational velocity that will allow the robot to re-orient itself during the fall to land on a predetermined target body segment (e.g., a backpack). The predetermined target body segment can be specially designed to absorb the impact of the fall and protect important components of the robot.

Abstract: A system and method is disclosed for controlling a robot having at least two legs, the robot subjected to an event such as a push that requires the robot to take a step to prevent a fall. In one embodiment, a current capture point is determined, where the current capture point indicates a location on a ground surface that is the current best estimate of a stepping location for avoiding a fall and for reaching a stopped state. The robot is controlled to take a step toward the current capture point. After taking the step, if the robot fails to reach a stopped state without taking any additional steps, an updated current capture point is determined based on the state of the robot after taking the step. The current capture points can be stored in a capture point memory and initialized based on a model of the robot.

Abstract: Systems and methods are presented that enable a legged robot to maintain its balance when subjected to an unexpected force. In the reflex phase, the robot withstands the immediate effect of the force by yielding to it. In one embodiment, during the reflex phase, the control system determines an instruction that will cause the robot to perform a movement that generates a negative rate of change of the robot's angular momentum at its centroid in a magnitude large enough to compensate for the destabilizing effect of the force. In the recovery phase, the robot recovers its posture after having moved during the reflex phase. In one embodiment, the robot returns to a statically stable upright posture that maximizes the robot's potential energy. In one embodiment, during the recovery phase, the control system determines an instruction that will cause the robot to perform a movement that increases its potential energy.

Abstract: Systems and methods are presented that use the rate of change of a legged robot's centroidal angular momentum ({dot over (H)}G) in order to maintain or improve the robot's balance. In one embodiment, a control system determines the current value of {dot over (H)}G, compares this value to a threshold value, and determines an instruction to send to the robot. Executing the instruction causes the robot to remain stable or become more stable. Systems and methods are also presented that use a value derived from {dot over (H)}G in order to maintain or improve the robot's balance. In one embodiment, a control system determines the location of the Zero Rate of change of Angular Momentum (ZRAM) point (A), determines the distance between A and the location of the center of pressure of the resultant ground force, compares this value to a threshold value, and determines an instruction to send to the robot.

Abstract: Systems and methods are presented that use the rate of change of a legged robot's centroidal angular momentum ({dot over (H)}G) in order to maintain or improve the robot's balance. In one embodiment, a control system determines the current value of {dot over (H)}G, compares this value to a threshold value, and determines an instruction to send to the robot. Executing the instruction causes the robot to remain stable or become more stable. Systems and methods are also presented that use a value derived from {dot over (H)}G in order to maintain or improve the robot's balance. In one embodiment, a control system determines the location of the Zero Rate of change of Angular Momentum (ZRAM) point (A), determines the distance between A and the location of the center of pressure of the resultant ground force, compares this value to a threshold value, and determines an instruction to send to the robot.

Abstract: A legged robot subjected to a force is controlled by determining an instantaneous capture point where the robot will step with a swing leg to reach a balanced home position, the balanced home position being a state in which the Center of Mass remains substantially over the Center of Pressure and the robot is able to maintain its balance indefinitely. The capture point can be determined using a Linear Inverted Pendulum Plus Flywheel (LIPPF) model of the robot. The LIPPF model includes a flywheel with a mass and a rotational inertia, and a variable length leg link. A torque profile is applied to the flywheel and a set of capture points is determined based on this torque profile An experimentally determined error value can be added to a capture point that is determined based on the model to account for differences between an actual robot and the model.

Abstract: Systems and methods are presented that enable a legged robot to maintain its balance when subjected to an unexpected force. In the reflex phase, the robot withstands the immediate effect of the force by yielding to it. In one embodiment, during the reflex phase, the control system determines an instruction that will cause the robot to perform a movement that generates a negative rate of change of the robot's angular momentum at its centroid in a magnitude large enough to compensate for the destabilizing effect of the force. In the recovery phase, the robot recovers its posture after having moved during the reflex phase. In one embodiment, the robot returns to a statically stable upright posture that maximizes the robot's potential energy. In one embodiment, during the recovery phase, the control system determines an instruction that will cause the robot to perform a movement that increases its potential energy.

Abstract: A system and method is disclosed for predicting a fall of a robot having at least two legs. A learned representation, such as a decision list, generated by a supervised learning algorithm is received. This learned representation may have been generated based on trajectories of a simulated robot when various forces are applied to the simulated robot. The learned representation takes as inputs a plurality of features of the robot and outputs a classification indicating whether the current state of the robot is balanced or falling. A plurality of features of the current state of the robot, such as the height of the center of mass of the robot, are determined based on current values of a joint angle or joint velocity of the robot. The current state of the robot is classified as being either balanced or falling by evaluating the learned representation with the plurality of features of the current state of the robot.

Abstract: Systems and methods are presented that enable a legged robot to maintain its balance when subjected to an unexpected force. In the reflex phase, the robot withstands the immediate effect of the force by yielding to it. In one embodiment, during the reflex phase, the control system determines an instruction that will cause the robot to perform a movement that generates a negative rate of change of the robot's angular momentum at its centroid in a magnitude large enough to compensate for the destabilizing effect of the force. In the recovery phase, the robot recovers its posture after having moved during the reflex phase. In one embodiment, the robot returns to a statically stable upright posture that maximizes the robot's potential energy. In one embodiment, during the recovery phase, the control system determines an instruction that will cause the robot to perform a movement that increases its potential energy.

Abstract: A system and method is disclosed for controlling a robot that is falling down from an upright posture. Inertia shaping is performed on the robot to avoid an object during the fall. A desired overall toppling angular velocity of the robot is determined. The direction of this velocity is based on the direction from the center of pressure of the robot to the object. A desired composite rigid body inertia of the robot is determined based on the desired overall toppling angular velocity. A desired joint velocity of the robot is determined based on the desired composite rigid body inertia. The desired joint velocity is also determined based on a composite rigid body inertia Jacobian of the robot. An actuator at a joint of the robot is then controlled to implement the desired joint velocity.

Abstract: A system and method is disclosed for controlling a robot having at least two legs, the robot falling down from an upright posture and the robot located near a plurality of surrounding objects. A plurality of predicted fall directions of the robot are determined, where each predicted fall direction is associated with a foot placement strategy, such as taking a step, for avoiding the surrounding objects. The degree to which each predicted fall direction avoids the surrounding objects is determined. A best strategy is selected from the various foot placement strategies based on the degree to which the associated fall direction avoids the surrounding objects. The robot is controlled to implement this best strategy.

Abstract: A system and method is disclosed for controlling a robot having at least two legs that is falling down from an upright posture. An allowable stepping zone where the robot is able to step while falling is determined. The allowable stepping zone may be determined based on leg Jacobians of the robot and maximum joint velocities of the robot. A stepping location within the allowable stepping zone for avoiding an object is determined. The determined stepping location maximizes an avoidance angle comprising an angle formed by the object to be avoided, a center of pressure of the robot upon stepping to the stepping location, and a reference point of the robot upon stepping to the stepping location. The reference point, which may be a capture point of the robot, indicates the direction of fall of the robot. The robot is controlled to take a step toward the stepping location.

Abstract: A system and method are presented to provide assist to a user by means of an exoskeleton with a controller capable of making the exoskeleton display active impedance. The exoskeleton assists the user by reducing the muscle effort required by the user to move his or her extremities. In one embodiment, a single-degree-of-freedom (1-DOF) exoskeleton assists a user with single-joint movement using an active impedance controller. In another embodiment, a multiple-degree-of-freedom (multi-DOF) exoskeleton assists a user with multiple-joint movement using an active impedance controller.