Stephen P. Buerger

Rehabilitation robotics: pilot trial of a spatial extension for MIT-Manus

BackgroundPrevious results with the planar robot MIT-MANUS demonstrated positive benefits in trials with over 250 stroke patients. Consistent with motor learning, the positive effects did not generalize to other muscle groups or limb segments. Therefore we are designing a new class of robots to exercise other muscle groups or limb segments. This paper presents basic engineering aspects of a novel robotic module that extends our approach to anti-gravity movements out of the horizontal plane and a pilot study with 10 outpatients. Patients were trained during the initial six-weeks with the planar module (i.e., performance-based training limited to horizontal movements with gravity compensation). This training was followed by six-weeks of robotic therapy that focused on performing vertical arm movements against gravity. The 12-week protocol includes three one-hour robot therapy sessions per week (total 36 robot treatment sessions).ResultsPilot study demonstrated that the protocol was safe and well tolerated with no patient presenting any adverse effect. Consistent with our past experience with persons with chronic strokes, there was a statistically significant reduction in tone measurement from admission to discharge of performance-based planar robot therapy and we have not observed increases in muscle tone or spasticity during the anti-gravity training protocol. Pilot results showed also a reduction in shoulder-elbow impairment following planar horizontal training. Furthermore, it suggested an additional reduction in shoulder-elbow impairment following the anti-gravity training.ConclusionOur clinical experiments have focused on a fundamental question of whether task specific robotic training influences brain recovery. To date several studies demonstrate that in mature and damaged nervous systems, nurture indeed has an effect on nature. The improved recovery is most pronounced in the trained limb segments. We have now embarked on experiments that test whether we can continue to influence recovery, long after the acute insult, with a novel class of spatial robotic devices. This pilot results support the pursuit of further clinical trials to test efficacy and the pursuit of optimal therapy following brain injury.

Complementary Stability and Loop Shaping for Improved Human–Robot Interaction

Robots intended for high-force interaction with humans face particular challenges to achieve performance and stability. They require low and tunable endpoint impedance as well as high force capacity, and demand actuators with low intrinsic impedance, the ability to exhibit high impedance (relative to the human subject), and a high ratio of force to weight. Force-feedback control can be used to improve actuator performance, but causes well-known interaction stability problems. This paper presents a novel method to design actuator controllers for physically interactive machines. A loop-shaping design method is developed from a study of fundamental differences between interaction control and the more common servo problem. This approach addresses the interaction problem by redefining stability and performance, using a computational approach to search parameter spaces and displaying variations in performance as control parameters are adjusted. A measure of complementary stability is introduced, and the coupled stability problem is transformed to a robust stability problem using limited knowledge of the environment dynamics (in this case, the human). Design examples show that this new measure improves performance beyond the current best-practice stability constraint (passivity). The controller was implemented on an interactive robot, verifying stability and performance. Testing showed that the new controller out-performed a state-of-the-art controller on the same system

Impedance and Interaction Control

Stephen P. Buerger Massachusetts Institute of Technology 19.

Relaxing Passivity for Human-Robot Interaction

Robots for high-force interaction with humans face particular challenges to achieve performance and coupled stability. Because available actuators are unable to provide sufficiently high force density and low impedance, controllers for such machines often attempt to mask the robots physical dynamics, though this threatens stability. Controlling for passivity, the state-of-the-art means of ensuring coupled stability, inherently limits performance to levels that are often unacceptable. A controller that imposes passivity is compared to a controller designed by a new method that uses limited knowledge of human dynamics to improve performance. Both controllers were implemented on a testbed, and coupled stability and performance were tested. Results show that the new controller can improve both stability and performance. The different structures of the controllers yield key differences in physical behavior, and guidelines are provided to assist in choosing the appropriate approach for specific applications

Characterization and control of a screw-driven robot for neurorehabilitation

The characterization and control of a module for a therapy robot is discussed. The screw-driven module expands the workspace of an existing robot used for neuro-rehabilitation from two to three dimensions. The need for low endpoint impedance in such devices is emphasized, and the factors influencing endpoint impedance are considered and evaluated for the new device. We evaluate the actuator and control system bandwidths and discuss a series of experiments to characterize the friction, gravitational force, and effective endpoint inertia. Several methods of active control for reducing effective endpoint impedance are explored and compared. Proportional force feedback was found to reduce impedance more effectively than model-based methods.

Novel Actuation Methods for High Force Haptics

Most haptic devices are intended primarily, if not exclusively, to exchange information with a human operator, and often replace or augment traditional computer displays with backdrivable, force-producing tactile interfaces. This includes popular commercial devices such as the PHANTOM (Massie & Salisbury, 1994) that are typically limited to at most several Newtons of endpoint force capacity, just enough to display simple virtual environments to the operator. Less conventional wearable haptic devices operate differently, but similarly have a low force capacity sufficient only to convey information (e.g. see devices described in (Biggs & Srinivasan, 2002)). By contrast, a class of applications that we refer to as high force haptics requires devices that exchange significant forces (and sometimes power) with an operator, often up to and exceeding the force to move limbs or even large fractions of body weight. While achieving high forces, these devices must also present low mechanical endpoint impedance to the operator (i.e. be backdrivable or feel “gentle”) in order to avoid injury and, frequently, to exchange information with the operator by representing virtual environments. We propose the following working definition:

In-Sole MEMS Pressure Sensing for a LowerExtremity Exoskeleton

The control system for the Berkeley lower extremity exoskeleton (BLEEX) requires ground contact pressure information to operate safely and effectively. Commercially available in-sole sensors do not have sufficient bandwidth, accuracy and reliability for such a system. We have designed and prototyped an in-sole ground contact sensor that uses MEMS pressure transducers placed in an array of hermetically sealed cavities. This system provides a robust method to monitor ground contact pressures

Using parallel stiffness to achieve improved locomotive efficiency with the Sandia STEPPR robot

In this paper we introduce STEPPR (Sandia Transmission-Efficient Prototype Promoting Research), a bipedal robot designed to explore efficient bipedal walking. The initial iteration of this robot achieves efficient motions through powerful electromagnetic actuators and highly back-drivable synthetic rope transmissions. We show how the addition of parallel elastic elements at select joints is predicted to provide substantial energetic benefits: reducing cost of transport by 30 to 50 percent. Two joints in particular, hip roll and ankle pitch, reduce dissipated power over three very different gait types: human walking, human-like robot walking, and crouched robot walking. Joint springs based on this analysis are tested and validated experimentally. Finally, this paper concludes with the design of two unique parallel spring mechanisms to be added to the current STEPPR robot in order to provide improved locomotive efficiency.

Parallel Elastic Elements Improve Energy Efficiency on the STEPPR Bipedal Walking Robot

This paper describes how parallel elastic elements can be used to reduce energy consumption in the electric-motor-driven, fully actuated, Sandia Transmission-Efficient Prototype Promoting Research (STEPPR) bipedal walking robot without compromising or significantly limiting locomotive behaviors. A physically motivated approach is used to illustrate how selectively engaging springs for hip adduction and ankle flexion predict benefits for three different flat-ground walking gaits: human walking, human-like robot walking, and crouched robot walking. Based on locomotion data, springs are designed and substantial reductions in power consumption are demonstrated using a bench dynamometer. These lessons are then applied to STEPPR, a fully actuated bipedal robot designed to explore the impact of tailored joint mechanisms on walking efficiency. Featuring high-torque brushless DC motors, efficient low-ratio transmissions, and high-fidelity torque control, STEPPR provides the ability to incorporate novel joint-level mechanisms without dramatically altering high-level control. Unique parallel elastic designs are incorporated into STEPPR, and walking data show that hip adduction and ankle flexion springs significantly reduce the required actuator energy at those joints for several gaits. These results suggest that parallel joint springs offer a promising means of supporting quasi-static joint torques due to body mass during walking, relieving motors of the need to support these torques and substantially improving locomotive energy efficiency.

The Sandia architecture for heterogeneous unmanned system control (SAHUC)

The Sandia Architecture for Heterogeneous Unmanned System Control (SAHUC) was produced as part of a three year internally funded project performed by Sandia’s Intelligent Systems, Robotics, and Cybernetics group (ISRC). ISRC created SAHUC to demonstrate how teams of Unmanned Systems (UMS) can be used for small-unit tactical operations incorporated into the protection of high-consequence sites. Advances in Unmanned Systems have provided crucial autonomy capabilities that can be leveraged and adapted to physical security applications. SAHUC applies these capabilities to provide a distributed ISR network for site security. This network can be rapidly re-tasked to respond to changing security conditions. The SAHUC architecture contains multiple levels of control. At the highest level a human operator inputs objectives for the network to accomplish. The heterogeneous unmanned systems automatically decide which agents can perform which objectives and then decide the best global assignment. The assignment algorithm is based upon coarse metrics that can be produced quickly. Responsiveness was deemed more crucial than optimality for responding to time-critical physical security threats. Lower levels of control take the assigned objective, perform online path planning, execute the desired plan, and stream data (LIDAR, video, GPS) back for display on the user interface. SAHUC also retains an override capability, allowing the human operator to modify all autonomous decisions whenever necessary. SAHUC has been implemented and tested with UAVs, UGVs, and GPS-tagged blue/red force actors. The final demonstration illustrated how a small fleet, commanded by a remote human operator, could aid in securing a facility and responding to an intruder.