Michael C. Yip

Model-Less Feedback Control of Continuum Manipulators in Constrained Environments

Continuum manipulators offer a means for robot manipulation in a constrained environment, where the manipulator body can safely interact with, comply with, and navigate around obstacles. However, obstacle interactions impose constraints that conform the robot body into arbitrary shapes regardless of actuator positions. Generally, these effects cannot be wholly sensed on a continuum manipulator and, therefore, render model-based controllers incorrect, leading to artificial singularities and unstable behavior. We present a task-space closed-loop controller for continuum manipulators that does not rely on a model and can be used in constrained environments. Using an optimal control strategy on a tendon-driven robot, we demonstrate this method, which we term model-less control, which allows the manipulator to interact with several constrained environments in a stable manner. To the best of our knowledge, this is the first work in controlling continuum manipulators without using a model.

Model-Less Hybrid Position/Force Control: A Minimalist Approach for Continuum Manipulators in Unknown, Constrained Environments

Continuum manipulators are designed to operate in constrained environments that are often unknown or unsensed, relying on body compliance to conform to obstacles. The interaction mechanics between the compliant body and unknown environment present significant challenges for traditional robot control techniques based on modeling these interactions exactly. In this letter, we describe a hybrid position/force control method that uses a model-less approach. Model-less control is a recently-described approach to control that learns the continuum manipulator Jacobian and adapts to constraints in the environment in a safe manner. When interacting with the environment using the end-effector, these tip-constraints can affect the manipulator Jacobian estimates to become ill-conditioned. This letter addresses this issue by defining a hybrid control approach for simultaneously controlling end-effector position and forces while still maintaining the minimalist approach of model-less control. Under this method, continuum manipulators can safely and effectively interact with the environment, even when these interactions are arbitrary and unknown constraints.

Modeling and Inverse Compensation of Hysteresis in Supercoiled Polymer Artificial Muscles

The supercoiled polymer (SCP) actuator is a recently discovered artificial muscle that demonstrates significant mechanical power, large contraction, and good dynamic range in a muscle-like form factor. There has been a rapid increase of research efforts devoted to the study of SCP actuators. For robotics, SCP actuators overcome specific challenges of artificial muscles such as shape memory alloy wires, where limited strain and slow dynamics, and power consumption had limited their use. It is known that hysteresis nonlinearity results from coiling the threads, and can cause up to 30% strain difference under the same voltage; however, no work has been reported to characterize the hysteresis in SCP actuators. In this paper, three new models are formulated to characterize the hysteretic relationship between three coupled variables (voltage input, strain, and load) of an SCP actuator, namely, the augmented generalized Prandtl–Ishlinskii model, the augmented Preisach model, and the augmented linear model. By incorporating the relationship between hysteresis curves and loading forces, the proposed models can efficiently characterize the hysteresis. Open-loop position control is further realized through inverse compensation. Experimental results show that the proposed schemes can effectively estimate and compensate the hysteresis. For the first time, the hysteresis characterization and compensation of SCP actuators are successfully demonstrated, such that accurate robot control can be realized.

Autonomous Control of Continuum Robot Manipulators for Complex Cardiac Ablation Tasks

Continuum manipulators enable minimally-invasive surgery on the beating heart, but the challenges involved in manually controlling the manipulator’s tip position and contact force with the tissue result in failed procedures and complications. The objective of this work is to achieve autonomous robotic control of a continuum manipulator’s position and force in a beating heart model. We present a model-less hybrid control approach that regulates the tip position/force of manipulators with unknown kinematics/mechanics, under unknown constraints along the manipulator’s body. The algorithms estimate the Jacobian in the presence of heartbeat disturbances and sensor noise in real time, enabling closed-loop control. Using this model-less control approach, a robotic catheter autonomously traced clinically relevant paths on a simulated beating heart environment while regulating contact force. A gating procedure is used to tighten the treatment margins and improve precision. Experimental results demonstrate the capabilities of the robot (1.4±1.1mm–1.9±1.4mm tracking error) while user demonstrations show the difficulty of manually performing the same task (2.6±2.0mm–4.3±3.9mm tracking error). This new, robotically-enabled contiguous ablation method could reduce ablation path discontinuities, improve consistency of treatment, and therefore improve clinical outcomes.

Erratum to: Six Degree-of-Freedom Measurements of Human Mild Traumatic Brain Injury.

FIDEL HERNANDEZ, LYNDIA C. WU, MICHAEL C. YIP, KAVEH LAKSARI, ANDREW R. HOFFMAN, JAIME R. LOPEZ, GERALD A. GRANT, SVEIN KLEIVEN, and DAVID B. CAMARILLO Department of Mechanical Engineering, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA; Department of Medicine, Stanford University, Stanford, CA, USA; Department of Neurology, Stanford University, Stanford, CA, USA; Department of Neurosurgery, Stanford University, Stanford, CA, USA; and Department of Neuronic Engineering, KTH Royal Institute of Technology, Stockholm, Sweden

Three-Dimensional Hysteresis Modeling of Robotic Artificial Muscles with Application to Shape Memory Alloy Actuators.

Robotic artificial muscles are increasingly popular in novel robotic applications. Their full utilization is challenged by the three-dimensional and coupled hysteresis nonlinearities among input, strain, and tension force. No prior studies on three-dimensional hysteresis models with coupled variables have been reported for robotic artificial muscles. This paper presents an approach to capturing and estimating the three-dimensional hysteresis in shape memory alloy (SMA) actuators. Experimental results confirm that the proposed scheme is effective. This study can be applied towards other robotic artificial muscles.