Canjun Yang

Hydrodynamics of an Undulating Fin for a Wave-Like Locomotion System Design

Motivated by the interest to develop an agile, high-efficiency robotic fish for underwater applications where safe environment for data-acquisition without disturbing the surrounding during exploration is of particular concern, this paper presents computational and experimental results of a biologically inspired mechanical undulating fin. The findings offer intuitive insights for optimizing the design of a fin-based robotic fish that offers several advantages including low underwater acoustic noise, dexterous maneuverability, and better propulsion efficiency at low speeds. Specifically, this paper begins with the design of a robotic fish developed for experimental investigation and for validating computational hydrodynamic models of an undulating fin. A relatively complete computational model describing the hydrodynamics of an undulating fin is given for analyzing the effect of propagating wave motions on the forces acting on the fin surface. The 3-D unsteady fluid flow around the undulating fin has been numerically solved using computational fluid dynamics method. These numerically simulated pressure and velocity distributions acting on the undulating fin, which provide a basis to compute the forces acting on the undulating fin, have been experimentally validated by comparing the computed thrust against data measured on a prototype flexible-fin mechanism.

Adaptive Knee Joint Exoskeleton Based on Biological Geometries

This paper presents a relatively complete analytical model of a knee joint interacting with a two-link exoskeleton for investigating the effects of different exoskeleton designs on the internal joint forces/torque in the knee. The closed kinematic chain formed by the leg and exoskeleton has a significant effect on the joint forces/torque in the knee. A bio-joint model is used to capture this effect by relaxing a commonly made assumption that approximates a knee joint as a perfect engineering pin-joint in designing an exoskeleton. Based on the knowledge of a knee-joint kinematics, an adaptive knee-joint exoskeleton has been designed to eliminate negative effects associated with the closed leg-exoskeleton kinematic chain on a human knee. For experimental validation, the flexion motion of an artificial human knee is investigated comparing the performances of five exoskeleton designs against the case with no exoskeleton. Analytical results that estimate internal forces/torque using the kinematic and dynamic models (based on the properties of a knee joint) agree well with data obtained experimentally. This investigation illustrates the applications of the analytical model for designing an adaptive exoskeleton that minimizes internal joint forces due to a knee-exoskeleton interaction.

A walking monitoring shoe system for simultaneous plantar-force measurement and gait-phase detection

This paper presents a walking-monitoring-shoe (WMS) system capable of simultaneous performing accurate plantar-force measurement and reliable gait-phase detection for continuous monitoring of human walking on treadmill. Based on anatomical information, the WMS employs four strain-gauges embedded in a homemade sole to accurately measure the contact force of the human foot exerted on the shoe-pad, and an efficient classification algorithm to detect five distinct gait-phases from the measured plantar force patterns. The WMS was experimentally evaluated, which has a typical 2nd-order system dynamics (with an 8% overshoot and a 2% settling time of 76ms when subject to a step input). Experimental results show that the accuracy and resolution of the sensing system are 1.09±0.09% (significant level=0.95) and 2N (0.2% of the maximal value of the load), respectively. The root-mean-square (rms) difference between the output signals of the WMS and the calibrated dynamic loading system was 1.67±0.12% (significant level=0.95). The feasibility of this integrated sensing/detection system was experimentally validated against video data, which relates gait-phases to the leg kinematics.

Model-based fuzzy adaptation for control of a lower extremity rehabilitation exoskeleton

Different gait patterns of stroke patients cannot be derived satisfactorily by traditional treadmill training robots. This paper presents a method to generate adaptive trajectories for controlling a lower extremity rehabilitation exoskeleton designed to help patients recover or improve walking ability. The model-based adaptation mechanism that consists of an inverse dynamic model, a trajectory generator and a fuzzy adaptation algorithm is proposed to minimize patients discomfort when active muscle contractions are not easily to be obtained. The effectiveness of the fuzzy adaptation algorithm, which accounts for the experience of a rehabilitation doctor, is demonstrated numerically with an illustrative example in this paper.

An adaptive knee joint exoskeleton based on biological geometries

This paper presents a dynamic model of a knee joint interacting with a two-link exoskeleton for investigating the effects of different exoskeleton designs on internal joint forces. The closed kinematic chain of the leg and exoskeleton has a significant effect on the joint forces in the knee. A bio-joint model is used to capture this effect by relaxing a commonly made assumption that approximates a knee joint as a perfect engineering pin-joint in exoskeleton design. Based on the knowledge of a knee-joint kinematics, an adaptive knee-joint exoskeleton has been designed by incorporating different kinematic components (such as a pin, slider and cam profile). This design potentially eliminates the negative effects associated with the closed leg/exoskeleton kinematic chain on a human knee. An investigation in the flexion motion of an artificial human knee joint is presented to compare performances of five exoskeleton designs against the case with no exoskeletons. Analytical results that estimate internal forces using the dynamic model (based on the properties of a knee joint) agree well with the experiments. These studies lead to an adaptive mechanism with a slider/cam as an alternative to pin joints for the exoskeleton, and illustrate the application of the model for designing an adaptive mechanism that minimizes internal joint forces due to a human-exoskeleton interaction.

Hydrodynamic modeling of an undulating fin for robotic fish design

Motivated by the interests to develop an agile, high-efficient robotic fish for underwater applications where safe environment for data-acquisition without disturbing the surrounding during exploration is of particular concern, this paper presents computational and experimental results of a biologically-inspired mechanical undulating-fin. The findings offer intuitive insights for optimizing the design of a fin-based robotic fish which has potentials to offer several advantages including low underwater acoustic noise, great maneuverability and better propulsion efficiency at low speeds. Specifically, this paper begins with the design of a robotic fish developed for experimental investigation and for validating computational hydrodynamic models of an undulating fin. A relatively complete computational model describing the hydrodynamics of an undulating fin is given. To analyze the effect of propagating wave motions on the forces acting on the fin surface, the three-dimensional unsteady fluid flow around the undulating fin is numerically solved using computational fluid dynamics (CFD) method. The pressure and velocity distributions acting on the undulating fin have been numerically simulated providing a basis to compute the forces acting on the undulating fin. The computational model has been experimentally validated by comparing the computed thrust coefficient against measured data based on a prototype flexible-fin mechanism.

Human finger mechanical impedance modeling: Using multiplicative uncertain model

To design a controller for the purpose of control of hand exoskeleton force, the critical question is to model the human finger impedance properly. The difficulty is that the parameters of the impedance model are perturbative in different postures. In this paper, multiplicative uncertain models of human finger impedance are presented. We describe the impedance as a mass-spring-damping system. The experiments are set in extension, half-flexion, flexion and synthesis postures. The parameters of nominal model as well as their perturbation range are identified by the forgetting factor recursive least square method. The weighting functions are constructed accordingly. The results show that the uncertain model of synthesis posture can represent the magnitude-frequency characteristic at low frequency, while, for high frequency, the uncertain models composed by the weighting function of synthesis posture and the corresponding nominal model are feasible. These provide effective approaches for hand exoskeleton force control issues.

Design of a low-cost underactuated finger for positioning or pinching thin objects

Robotic grippers in industry are expected to have low degrees of freedom (DOFs) with cost and simplicity concerns. However, thin objects (e.g. mobile phone covers, shielding of IC chips) cannot be handled by traditional gripper fingers, since deformation may be caused. To solve this problem, a low-cost underactuated finger with a special four-bar linkage and a flexible joint is proposed in this paper. The special four-bar linkage is designed to obtain the desirable motion trail of the fingertip which is a quasi-horizontal line, while the flexible joints reduce the impact force and achieve compliant force control. In this paper, the design methodology of the four-bar linkage and the flexible joint is introduced, while the kinematic performance is analyzed. An experiment was conducted to verify the design and analysis. Results show that the proposed two DOFs underactuated finger can be applied on a robotic gripper to pinch or position thin objects. Finally, an example for its application is briefly explained to reinforce the concept.