Amor Jnifene

Design and control of a shape memory alloy based dexterous robot hand

Modern externally powered upper-body prostheses are conventionally actuated by electric servomotors. Although these motors achieve reasonable kinematic performance, they are voluminous and heavy. Deterring factors such as these lead to a substantial proportion of upper extremity amputees avoiding the use of their prostheses. Therefore, it is apparent that there exists a need for functional prosthetic devices that are compact and lightweight. The realization of such a device requires an alternative actuation technology, and biological inspiration suggests that tendon based systems are advantageous. Shape memory alloys are a type of smart material that exhibit an actuation mechanism resembling the biological equivalent. As such, shape memory alloy enabled devices promise to be of major importance in the future of dexterous robotics, and of prosthetics in particular. This paper investigates the design, instrumentation, and control issues surrounding the practical application of shape memory alloys as artificial muscles in a three-fingered robot hand.

Active vibration control of flexible structures using delayed position feedback

The paper discusses the use of a simple position control system approach to improve the performance of lightly damped dynamic systems. This approach uses a delayed position feedback signal to actively control the vibrations of flexible structures. A complete analysis of the stability of a single-link flexible manipulator under time delay control is presented and critical values of time delay for a given controller gain have been determined. The paper also presents a short comparison between the delayed feedback signal control and the linear quadratic regulator.

Multiple Waypoint Path Planning for a Mobile Robot using Genetic Algorithms

This investigation developed a MATLAB program, based on genetic algorithms that generated an optimal (shortest distance) path plan for a mobile robot to visit all of the specified waypoints without colliding with the known obstacles. The designed genetic algorithm path planner was shown to accomplish this task and produce superior results when compared against a full search path planner. Next, it was shown that the choice of search parameters for the genetic algorithm effected the time to execute the search and the quality of the solution (length of the chosen path). Having proven the genetic algorithm path planner in simulation, the genetic algorithm path planner then successfully guided an actual X80 mobile robot to all its waypoints without colliding with any obstacles in a test environment

An Experimental Study on a SMA Driven Pressurized Hyper-redundant Manipulator:

This study describes the design and fabrication of a pressurized hyper-redundant manipulator driven by high strain shape memory alloy (SMA) actuators. Hyper-redundant devices are characterized by repeating independently controlled structures connected in series; their architecture is comparable to that of a snake or worm. The proposed design is composed of four identical modules; each providing three degrees of freedom from three symmetrically positioned actuators. The manipulator stiffness and actuator return-force are controlled by pressurized air, injected at the base of the manipulator. Tests on a single unit module have demonstrated that the design could achieve rotations of over 50° and displacements of over 40% at a frequency of 1/20 Hz.

Fuzzy Logic Control of the End-Point Vibration in an Experimental Flexible Beam

This paper is concerned with the design and implementation of a fuzzy logic controller (FLC) to control the end-point vibration in a single flexible beam mounted on a two-degrees-of-freedom platform. The angular position of the hub and the signal from a strain gage mounted on the beam are used as the two inputs to the FLC. In order to add more damping, the strain gage signal is combined with the hub angular velocity represented by the output of a tachometer attached to the motor shaft. We discuss how to build the rule base for the flexible beam based on the relation between the angular displacement of the hub and the end-point deflection, as well as the effect of different scaling gains on the performance of the FLC. We present several experimental results showing the effectiveness of the FLC in reducing the end-point vibration of the flexible beam.

A Study on the Thermomechanical Properties of Shape Memory Alloys-based Actuators used in Artificial Muscles

Shape memory alloys (SMAs) are a class of smart material having the unique ability to return to a predefined shape when heated. These materials are employed in a variety of emerging applications, and may potentially be used to avoid traditionally voluminous and heavy prosthetic actuators. The primary focus of this article is to convey the design and evaluation of a compact, lightweight, and high-strain SMA ribbon-based artificial muscle for use in such biomimetic applications. A key factor in the design of such an actuator is a thorough understanding of the thermomechanical response of the shape memory material. As such, a review of the relevant constitutive models is included. A selected hysteresis model is evaluated for potential application to ribbon type elements. The proposed actuator achieves strains of 31.6%; a marked improvement over previously documented SMA-based actuators.

Development, validation, and parameter sensitivity analyses of a nonlinear mathematical model of air springs

Air springs are highly nonlinear devices. Linear and quasi-linear models of air springs have been developed over the years to analyze and predict their behavior. Such models are shown here to be inadequate to describe the behavior of this highly nonlinear element. A nonlinear mathematical model of air springs has been developed and reported in this paper. The model has been verified experimentally, and has been shown to be effective in predicting the behavior of air springs. The sensitivity of the model to uncertainties in two key parameters is examined.

Environment mapping using probabilistic quadtree for the guidance and control of autonomous mobile robots

This paper presents the implementation of an environment mapping technique based on a probabilistic quadtree which records the location of static and dynamic obstacles, as well as the certainty over each obstacles estimated position. The quadtree-based map is updated online (i.e. near-real time) based on multi-sensor feeds originating from one to three X80 mobile robots operating simultaneously. The probabilistic quadtree map is part of a guidance and navigation control system which combines a Genetic Algorithm-based global path planner and a Potential Field local controller. The centralized map is shared by all mobile robots although each robot has an independent controller. Performance of the proposed method for this guidance and navigation control system is demonstrated experimentally with the Dr. Robots ™ wireless X80 mobile robots.

Biologically inspired anthropomorphic arm and dextrous robot hand actuated by smart-material-based artificial muscles

Shape memory alloys (SMA) are a class of smart material having the unique ability to return to a predefined shape when heated. SMA based actuators have the potential to be very compact and low weight. As a result, much research has been devoted to the design of SMA based actuators; however, commercialization has been largely impeded by the small strain capacity inherent to SMA. To address this deficiency, this paper conveys the design of a large-strain SMA actuator (in excess of 30%) whose feasibility is investigated by integrating the actuators as artificial muscles in a two link anthropomorphic arm. The ensuing experimental results indicate that the actuators show great potential for a variety of emerging applications. Finally the design of an SMA based dextrous robotic hand evaluation facility is proposed, and provides a case study illustrating how smart structures provide a superior alternative to conventionally voluminous and heavy prosthetic actuators.

Environment mapping using hybrid octree knowledge for UAV trajectory planning

In addressing the need for enhanced autonomous unmanned aerial vehicle (UAV) controllers, this work presents a knowledge base providing a synthetic representation of the UAV’s environment, enabling autonomous trajectory planning. The knowledge base uses a memory-efficient hybrid structure combining octree and standard three-dimensional maps. Essential elements including terrain, obstacles, and atmospheric conditions are mapped in 3D through layers grafted onto the octree structure. The knowledge base also integrates the capability of adding user-defined layers to represent mission-dependent features such as radar exposure or communication link intensity.