Florida Institute for Human and Machine Cognition, Inc.

Other

Honda Motor Co., Ltd.

Florida Institute for Human & Machine Cognition, Inc. (Ihmc)

Jerry E Pratt

Timothy L Hutcheson

Ambarish Goswami

John Rebula

Christopher John Morse

Benjamin Thomas Krupp

Aaron G Flores

Twan Koolen

Fabian Canas

An apparatus and a method for robotic control that allows an unbalanced pendulum robot to raise its Center of Mass and balance on two motorized wheels. The robot includes a pair of arms that are connected to the upper body of the robot through motorized joints. The method consists of a series of movements employing the arms of the robot to raise the robot to the upright position. The method comprises a control loop in which the motorized drives are included for dynamic balance of the robot and the control of the arm apparatus. The robot is first configured as a low Center of Mass four-wheeled vehicle, then its Center of Mass is raised using a combination of its wheels and the joint located at the attachment point of the arm apparatus and the robot body, between the rear and front wheels; the method then applies accelerations to the rear wheels to dynamically pivot and further raise the Center of Mass up and over the main drive wheels bringing the robot into a balancing pendulum configuration.

Reconfigurable balancing robot and method for moving over large obstacles

A control system for a bipedal humanoid robot that utilizes certain fundamental characteristics of bipedal motion to provide a robust and relatively simple balancing and walking mechanism. The system primarily utilizes the concept of 'capturability,' which is defined as the ability of the robot to come to a stop without falling by taking N or fewer steps. This ability is considered crucial to legged locomotion and is a useful, yet not overly restrictive criterion for stability. In the preferred embodiment, the bipedal robot is maintained in a 1-step capturable state. This means that future step-locating and driving decisions are made so that the robot may always be brought to a balanced halt with the taking of one step. Other embodiments maintain the bipedal robot in an N-step capturable state, in which the robot may always be brought to a balanced halt by taking N or fewer steps.

Humanoid robot that can dynamically walk with limited available footholds in the presence of disturbances

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.

Learning capture points for humanoid push recovery

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.

Determination of foot placement for humanoid push recovery

Reconfigurable balancing robot and method for dynamically transitioning between statically stable mode and dynamically balanced mode

An actuator and control algorithm which provide an operator with the ability to intuitively and responsively maneuver heavy work-pieces with ease and precision. The structure of the apparatus may provide a hoist with a compliant sensing system to measure the weight of the payload. The compliant sensing system may result in smaller dead-bands than are realizable with traditional force sensing methods. At the command of the user, the control algorithm may switch between two distinct operational modes: float mode and manual mode. In float mode, the hoist actively counterbalances the weight of the load, allowing it to feel substantially weightless in the operator's hands. The operator can apply forces directly to the payload to accelerate it in the desired vertical direction. Because of the small dead-band realized with compliant sensing, the payload may be highly responsive to the operators force inputs. As a result, the payload may be intuitively maneuvered at very high speeds, as well as very low speeds. Alternately, the operator may choose to operate in manual mode. While in manual mode, the hoist operates like traditional lifting hoists, responding to velocity commands issued from a remotely controlled pendant.

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Pensacola, FL, United States of America

Jerry E Pratt