Model-Based Neuromechanical Controller for a Robotic Leg

• US 20100324699A1
• Filed: 02/01/2010
• Published: 12/23/2010
• Est. Priority Date: 03/31/2005
• Status: Active Grant

• Current Assignee: Massachusetts Institute of Technology
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Geyer, Hartmut, Eilenberg, Michael Frederick, Herr, Hugh M.
• Granted Patent: US 8,864,846 B2
• Time in Patent Office: Days
• US Class Current: 623/27
• CPC Class Codes: A61F 2/605 Hip joints
• CPC Class Codes: A61F 2/64 Knee joints
• CPC Class Codes: A61F 2/66 Feet; Ankle joints
• CPC Class Codes: A61F 2/70 electrical
• CPC Class Codes: A61F 2/74 fluid , i.e. hydraulic or pneumatic
• CPC Class Codes: A61F 2/741 using powered actuators, e.g. stepper motors or solenoids
• CPC Class Codes: A61F 2002/701 operated by electrically controlled means, e.g. solenoids or torque motors
• CPC Class Codes: A61F 2002/704 computer-controlled, e.g. robotic control
• CPC Class Codes: A61F 2002/705 Electromagnetic data transfer for implantable prostheses A61F2250/0002
• CPC Class Codes: A61F 2002/7625 for measuring angular position
• CPC Class Codes: A61F 2002/7635 for measuring force, pressure or mechanical tension
• CPC Class Codes: A61F 2002/764 for measuring acceleration
• CPC Class Codes: A61F 2002/7645 for measuring torque, e.g. hinge or turning moment, moment of force
• CPC Class Codes: A61F 2005/0155 with actuating means
• CPC Class Codes: A61F 5/0123 for the knees A61F5/0106 takes precedence
• CPC Class Codes: A61F 5/0127 for the feet A61F5/0111 takes precedence
• CPC Class Codes: B25J 9/0006 Exoskeletons, i.e. resembling a human figure
• CPC Class Codes: B25J 9/1075 with muscles or tendons
• CPC Class Codes: B25J 9/1633 compliant, force, torque control, e.g. combined with position control
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A model-based neuromechanical controller for a robotic limb having at least one joint includes a finite state machine configured to receive feedback data relating to the state of the robotic limb and to determine the state of the robotic limb, a muscle model processor configured to receive state information from the finite state machine and, using muscle geometry and reflex architecture information and a neuromuscular model, to determine at least one desired joint torque or stiffness command to be sent to the robotic limb, and a joint command processor configured to command the biomimetric torques and stiffnesses determined by the muscle model processor at the robotic limb joint. The feedback data is preferably provided by at least one sensor mounted at each joint of the robotic limb. In a preferred embodiment, the robotic limb is a leg and the finite state machine is synchronized to the leg gait cycle.

Claims

1. A model-based neuromechanical controller for a robotic limb comprising at least one joint, the controller comprising:

a muscle model processor, the muscle model processor being configured to receive feedback data relating to the state of the robotic limb and, using muscle geometry and reflex architecture information, to determine at least one desired joint torque or impedance command to be applied to the robotic limb; and

a joint command processor, the joint command processor being configured to apply the biomimetic torques or impedances determined by the muscle model processor to at the robotic limb joint.

2. The controller of claim 1, wherein the feedback data is provided by at least one sensor mounted at each joint of the robotic limb.

3. The controller of claim 1, wherein the robotic limb is a leg and further comprising a finite state machine is synchronized to the leg gait cycle.

4. The controller of claim 3, the leg comprising a powered ankle-foot prosthesis.

5. The controller of claim 3, the leg comprising a knee joint.

6. The controller of claim 4, the leg further comprising a knee joint.

7. The controller of claim 6, the leg further comprising a hip joint.

8. The controller of claim 2, wherein at least one sensor is an angular joint displacement and velocity sensor, a torque sensor, or an inertial measurement unit.

9. A method for controlling a robotic limb comprising at least one joint, the method comprising the steps of:

receiving feedback data relating to the state of the robotic limb;

determining, using a neuromuscular model, comprising muscle geometry and reflex architecture information, and the state information, at least one desired joint torque or impedance command to be applied to the robotic limb; and

applying the biomimetic torques and impedances determined by the neuromuscular model processor at the robotic limb joint.