Eileen Lee Ming Su

Micromanipulation accuracy in pointing and tracing investigated with a contact-free measurement system

This study examines micromanipulation accuracy in pointing and in tracing a circle, using a novel contact-free measurement system. Three groups of subjects enable us to investigate the influence of age and micromanipulation expertise. The results show that, for all groups of subjects, a 10x magnification increases accuracy, but larger magnification does not improve it further. Expertise leads to reduced error, and grip force does not affect accuracy in the magnified condition.

Effect of Grip Force and Training in Unstable Dynamics on Micromanipulation Accuracy

This paper investigates whether haptic error amplification using unstable dynamics can be used to train accuracy in micromanipulation. A preliminary experiment first examines the possible confounds of visual magnification and grip force. Results show that micromanipulation precision is not affected by grip force in both naive and experienced subjects. On the other hand, precision is increased by visual magnification of up to 10×, but not further for larger magnifications. The main experiment required subjects to perform small-range point-to-point movements in 3D space in an unstable environment which amplified position errors to the straight line between start and end point. After having trained in this environment, subjects performing in the free conditions show an increase in success rate and a decrease in error and its standard deviation relative to the control subjects. This suggests that this technique can improve accuracy and reliability of movements during micromanipulation.

Development of CR2-Haptic: A compact and portable rehabilitation robot for wrist and forearm training

Stroke has now become the leading cause of severe disability. Rehabilitation robots are gradually becoming popular for stroke rehabilitation to improve motor recovery, as robotic technology can assist, enhance, and further quantify rehabilitation training for stroke patients. However, most of the available rehabilitation robots are complex and involve multiple degrees-of-freedom (DOFs) causing it to be very expensive and huge in size. Rehabilitation robots should be useful but also need to be affordable and portable enabling more patients to afford and train independently at home. This paper presents a development of an affordable, portable and compact rehabilitation robot that implements different rehabilitation strategies for stroke patient to train forearm and wrist movement in an enhanced virtual reality environment with haptic feedback.

A novel haptic interface and control algorithm for robotic rehabilitation of stoke patients

Rehabilitation robots are gradually becoming popular for stroke rehabilitation to improve motor recovery. By using a robot, the patient may perform the training more frequently on their own, but they must be motivated to do so. Therefore, this project develops a set of rehabilitation training programs with different haptic modalities on Compact Rehabilitation Robot (CR2) - a robot used to train upper and lower limbs reaching movement. The paper present the developed haptic interface, Haptic Sense with five configurable haptic modalities that include sensations of weight, wall, spring, sponge and visual amplification. A combination of several haptic modalities was implemented into virtual reality games, Water Drop - a progressive training game with up to nine levels of difficulties that requires user to move the cup to collect the water drops.

Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects

Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This paper implements the concept of a modular and reconfigurable robot, reducing its cost and size by adopting different therapeutic end effectors for different training movements using a single robot. The challenge is to increase the robot’s portability and identify appropriate kinds of modular tools and configurations. Because literature on the effectiveness of this kind of rehabilitation robot is still scarce, this paper presents the design of a portable and reconfigurable rehabilitation robot and describes its use with a group of post-stroke patients for wrist and forearm training. Seven stroke subjects received training using a reconfigurable robot for 30 sessions, lasting 30 min per session. Post-training, statistical analysis showed significant improvement of 3.29 points (16.20%, p = 0.027) on the Fugl-Meyer assessment scale for forearm and wrist components. Significant improvement of active range of motion was detected in both pronation-supination (75.59%, p = 0.018) and wrist flexion-extension (56.12%, p = 0.018) after the training. These preliminary results demonstrate that the developed reconfigurable robot could improve subjects’ wrist and forearm movement.

Accurate micromanipulation induced by performing in unstable dynamics

This study examines effects of learning 3D micromanipulation in an unstable dynamic environment. A test group trained in an unstable divergent force field while a control group trained the movement in the null force field. The subjects in the test group increased the success rate, in contrast to the control group which had similar rate after training. The error and its standard deviation decreased in the test group but not in the control group. In summary, training in unstable dynamics enable subjects to become more accurate, in contrast to training using only visual feedback.

Gaussian pedestrian proxemics model with social force for service robot navigation in dynamic environment

Pedestrian motion behaves stochastically, causing difficulties in modelling the appropriate proxemics for effective and efficient service robot navigation. Intruding the pedestrian social space can affect the social acceptance of a service robot. In this paper, a new proxemics model, Social-Force Gaussian Pedestrian Proxemics Model is presented to model the pedestrian social space and to improve the service robot navigation in dynamic human environment. This model was simulated and validated in a pedestrian simulator with both low and high pedestrian density environments. Results showed that the proposed model (i) improved proxemics representation of pedestrians, (ii) enhanced the robot performance in respecting the social norm and (iii) increased the efficiency in achieving a given task. This paper also presents the methods for parameter selections for the model without the requirement of complex tuning.

Low cost sensor data fusion in omnidirectional mobile robot feedback system to improve the navigation accuracy

Omnidirectional mobile robot has gained popularity among researchers. However, omnidirectional mobile robot is rarely been applied in industry field especially in the factory which is relatively more dynamic than normal research setting condition. Hence, it is very important to have a stable yet reliable feedback system to allow a more efficient and better performance controller on the robot. In order to ensure the reliability of the robot, many of the researchers use high cost solution in the feedback of the robot. For example, there are researchers use global camera as feedback. This solution has increases the cost of the robot setup fee to a relatively high amount. The setup system is also hard to modify and lack of flexibility. In this paper, a novel sensor fusion technique is proposed and the result is discussed.

Comparison between Normal Waveform and Modified Wavefront Path Planning Algorithm for Mobile Robot

Mobile robot path planning is about finding a movement from one position to another without collision. The wavefront is typically used for path planning jobs and appreciated for its efficiency, but it needs full wave expansion which takes significant amount of time and process in large scale environment. This study compared wavefront algorithm and modified wavefront algorithm for mobile robots to move efficiently in a collision free grid based static environment. The algorithms are compared in regards to parameters such as execution time of the algorithm and planned path length which is carried out using Player/Stage simulation software. Results revealed that modified wavefront algorithm is a much better path planning algorithm compared to normal wavefront algorithm in static environment.

Improvement of automated guided vehicle design using finite element analysis

Automated Guided Vehicle is a mobile robot used in various industries to transfer goods and materials from one place to another in the industrial compound such as production line and warehouses. Due to the payload it should carry, the design should be able to handle certain level of mechanical stress. The optimization study is important to assure the material and design is safe an optimum under the specified conditions before the AGV is manufactured. In this study, a conventional AGV designed previously by an AGV manufacturer to bring a payload of 70 kg is analyzed using the Finite Element Method (FEM) and SolidWorks software is used to do the FEA simulation. This paper also explain on how the factor of safety for the AGV is derived. The parameter change in this study were the thickness of the sheet metal used to build the AGV while the study output is the stress level, factor of safety and weight of the AGV.