Assistive Control

Objectives and Significance

The project addresses the fundamental problem of how to control the motion of a robot so that it can cooperatively work with humans to assist them in repetitive tasks. Oscillatory body movements constitute an elementary means for various tasks in human living. Such repetitive movements include essential life functions such as heart beat, breathing, eating (chewing), walking; basic daily tasks such as brushing teeth, washing face; house-hold chores such as cleaning windows, sweeping floor; health/entertainment activities such as dancing, swimming, cycling, rowing; and manufacturing labors such as moving objects in factory assembly lines. Robots and mechanical devices that assist such human movements would be found useful in a number of contexts. A robotic manipulator and a human arm may grab a common tool to work together on repetitive tasks where the former assists the latter by providing force and stability to reduce burden on the human. An exoskeleton may be worn to complement reduced capability of, or provide rehabilitation for, elderly people and patients with neurological disorders or physical disabilities. Thus, well-designed assistive devices for oscillatory movements would significantly contribute to improving quality of human life. Design of robotic mechanisms for such assistive devices is surely a challenging task. Equally challenging is the design of control algorithms that command the actuators and govern the motion of the robotic device. The state-of-the-art control technologies allow a designer to program a robot to achieve prescribed motion with speed, precision, and robustness, as seen for instance in industrial manipulators. However, if such robots interact with humans, they would be perceived as stiff, stubborn, or even dangerous, and are therefore not suitable as co-robots in direct support of humans. What is needed is control algorithms that make robots understand human intentions, cooperate with humans without insisting on their preprogramed operations, and assist with human tasks. Development of such algorithms is the focus of this project.

This basic research aims to establish a systematic method for designing a feedback controller for a general robotic system interacting with a human to stabilize the oscillation intended by the human and to reduce the burden on the human by providing assistive forces. The control architecture is inspired by the central pattern generator (CPG) -- neuronal circuits that command muscle contractions to achieve rhythmic body movements during animal locomotion. CPGs are attractive for engineering applications due to its ability to conform their oscillations to natural dynamics of a varying environment through sensory feedback. This exploratory research investigates the potential of the CPG architecture to provide a viable foundation for a new system design for achieving co-robots that assist humans to execute oscillation tasks.

Results

We consider the situation where a human applies a force to a single degree-of-freedom (DOF) robotic system, loaded by a resistive environment, to achieve an intended harmonic motion. A design problem is formulated for the CPG control to drive the system and stabilize the human-intended oscillation while reducing the human burden. Motivated by the mechanism of the reciprocal inhibition oscillator (RIO) to achieve robust entrainment to a natural oscillation, we first derived a condition for the RIO controller to achieve a damping compensation approximately. The nonlinear closed-loop robot-RIO-human system is then analyzed to give a sufficient condition for stability of the human-intended harmonic motion, assuming that the human motor control can be modeled as a combination of feedforward and feedback terms. The model-based analysis has shown that the control design does not require precise knowledge of the human model, and the stability is guaranteed if the human control satisfies a certain qualitative property. This has led to a design procedure that is essentially model-free.

The proposed RIO control scheme is validated through physical experiments on a simple robotic arm under resistive loading by a high viscosity fluid. The system emulates a situation where a human and a robot grab a common tool to stir viscous fluids. We first performed a system identification for the human motor control under various loading conditions and examined plausibility of the hybrid human control model and satisfaction of the stability condition. We then designed a CPG-based assistive controller and demonstrated its performance in reducing the human effort. During the validation process, a computer screen shows a reference target position and the actual position of the robotic arm. A human grabs the robotic arm and moves it to follow the reference. The task of the controlled robotic arm is to help the human and reduce the human force required to counteract the resistive load. The experimental data shows that the human force can be significantly reduced by turning the RIO control on.

The assistive RIO control method is currently being extended to deal with multi-DOF robotic systems. The idea is to place an RIO control for each DOF to compensate for resistive forces. The challenge is to coordinate multiple motion variables without inducing resonance between them. The design theory will be tested against a two-DOF parallel linkage system.

References

CPG Control for Periodic Motion of Assistive Robot with Human Motor Control Identification

J. Zhao and T. Iwasaki, IEEE Transactions on Control Systems Technology, 2019 (To appear), accepted version

CPG Control for Assisting Human with Periodic Motion Tasks

J. Zhao and T. Iwasaki, IEEE Conference on Decision and Control, pp.5035-5040, 2016.

Bio-inspired Control of Robots to Assist Humans with Repetitive Movement Tasks

Jinxin Zhao, Ph.D Dissertation, UCLA, December 2017

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