Oscar Chuy

Bio: Oscar Chuy is an academic researcher from Florida State University. The author has contributed to research in topics: Motion control & Kinematics. The author has an hindex of 12, co-authored 25 publications receiving 508 citations. Previous affiliations of Oscar Chuy include Florida A&M University – Florida State University College of Engineering & Tohoku University.

Analysis and Experimental Verification for Dynamic Modeling of A Skid-Steered Wheeled Vehicle

Abstract: Skid-steered vehicles are often used as outdoor mobile robots due to their robust mechanical structure and high maneuverability. Sliding, along with rolling, is inherent to general curvilinear motion, which makes both kinematic and dynamic modeling difficult. For the purpose of motion planning, this paper develops and experimentally verifies dynamic models of a skid-steered wheeled vehicle for general planar (2-D) motion and for linear 3-D motion. These models are characterized by the coefficient of rolling resistance, the coefficient of friction, and the shear deformation modulus, which have terrain-dependent values. The dynamic models also include motor saturation and motor power limitations, which enable correct prediction of vehicle velocities when traversing on hills. It is shown that the closed-loop system that results from inclusion of the dynamics of the [proportional--integral--derivative (PID)] speed controllers for each set of wheels does a much better job than the open-loop model of predicting the vehicle linear and angular velocities. For a vehicle turning with small linear and angular accelerations, the model provides accurate predictions of velocities and reasonable predictions of torques. Hence, the closed-loop model is recommended for motion planning.

A New Control Approach for a Robotic Walking Support System in Adapting User Characteristics

Abstract: This paper proposes a new control approach for a robotic walking support system to adapt a user's controlling characteristic. The control approach will be implemented by changing the kinematic structure of the robotic walking support system based on a variable center of rotation. This new control approach aims to help users who have difficulties in controlling their walking support system. In this study, we have a training stage to evaluate and adapt user's controlling characteristics. This will be implemented by allowing the user to follow some training paths. In the event a large path error occurs, a learning algorithm will vary the center of rotation of the support system until the user can successfully follow the training path. The relationship between the user intent in the form of applied force/torque and the new center of rotation will be taken by considering several training paths. This relationship will be used in actual control of the robotic walking support system. Experimentation and evaluation are presented to show the validity of the proposed control algorithm

A Control Approach Based on Passive Behavior to Enhance User Interaction

Abstract: This paper proposes a new control approach for an active (motorized) robotic walking support system based on passive behavior concept. The control approach aims to enhance the interaction between the support system and the user. The passive behavior of a support system allows the user to safely interact with the system since it removes the system's capability to move when there is no user's intention. This passive behavior is realized using imposed apparent dynamics, which uses the user's intention represented by the applied force/torque to derive the system's desired motion. The control approach is extended into a user-oriented motion control algorithm to adapt user's controlling characteristics. This is implemented by varying the point of application of the apparent dynamics. The control approach is further extended to use environment information and realize environment feedback concept. This is implemented by varying the parameters of the apparent dynamics based on environment data. Experimental results are presented to show the validity of the proposed control approach.

Approach in Assisting a Sit-to-Stand Movement Using Robotic Walking Support System

Abstract: This paper presents an approach in assisting a sit-to-stand movement using a robotic walking support system. In general, robotic walking support system is used to provide walking stability. We will extend its function to assist a user in executing a sit-to-stand movement. The first approach would be called passive support. In this approach, the support system would be stationary as the user execute the sit-to-stand movement. The knee torque would be determined and this would be compared to a sit-to-stand movement without support. The second approach would be called active support and the knee torque would be supported. A motion control algorithm would be proposed such that the support system will move based on the supporting torque. The actual experimentation on both approaches in assisting a sit-to-stand movement will be presented. The experimental result on active support shows the validity of the proposed motion control algorithm

Power modeling of a skid steered wheeled robotic ground vehicle

Abstract: Analysis of the power consumption of a robotic ground vehicle (RGV) is important for planning since it enables motion plans that do not violate the power limitations of the motors, energy efficient path planning, prediction of the ability to complete a task based upon the vehicle's current energy supply, and estimation of when the vehicle will need to refuel or recharge. Power modeling is particularly difficult for skid steered vehicles because of the complexities of properly taking into account the skidding that is used for vehicle turning. This paper begins with a 2-dimensional, second order differential equation of a skid steered, wheeled RGV and shows that the power model is terrain dependent and is a function of both the turning radius and linear velocity of the vehicle. This model was verified experimentally, and a comprehensive set of experiments was performed to describe the power consumption of a skid steered RGV on asphalt.

Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers

Abstract: The use of on-body wearable sensors is widespread in several academic and industrial domains. Of great interest are their applications in ambulatory monitoring and pervasive computing systems; here, some quantitative analysis of human motion and its automatic classification are the main computational tasks to be pursued. In this paper, we discuss how human physical activity can be classified using on-body accelerometers, with a major emphasis devoted to the computational algorithms employed for this purpose. In particular, we motivate our current interest for classifiers based on Hidden Markov Models (HMMs). An example is illustrated and discussed by analysing a dataset of accelerometer time series.

Kalman Filter for Robot Vision: A Survey

Abstract: Kalman filters have received much attention with the increasing demands for robotic automation. This paper briefly surveys the recent developments for robot vision. Among many factors that affect the performance of a robotic system, Kalman filters have made great contributions to vision perception. Kalman filters solve uncertainties in robot localization, navigation, following, tracking, motion control, estimation and prediction, visual servoing and manipulation, and structure reconstruction from a sequence of images. In the 50th anniversary, we have noticed that more than 20 kinds of Kalman filters have been developed so far. These include extended Kalman filters and unscented Kalman filters. In the last 30 years, about 800 publications have reported the capability of these filters in solving robot vision problems. Such problems encompass a rather wide application area, such as object modeling, robot control, target tracking, surveillance, search, recognition, and assembly, as well as robotic manipulation, localization, mapping, navigation, and exploration. These reports are summarized in this review to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed in an abstract level.

Progress and prospects of the human---robot collaboration

Abstract: Recent technological advances in hardware design of the robotic platforms enabled the implementation of various control modalities for improved interactions with humans and unstructured environments. An important application area for the integration of robots with such advanced interaction capabilities is human---robot collaboration. This aspect represents high socio-economic impacts and maintains the sense of purpose of the involved people, as the robots do not completely replace the humans from the work process. The research community's recent surge of interest in this area has been devoted to the implementation of various methodologies to achieve intuitive and seamless human---robot-environment interactions by incorporating the collaborative partners' superior capabilities, e.g. human's cognitive and robot's physical power generation capacity. In fact, the main purpose of this paper is to review the state-of-the-art on intermediate human---robot interfaces (bi-directional), robot control modalities, system stability, benchmarking and relevant use cases, and to extend views on the required future developments in the realm of human---robot collaboration.

Human-Walking-Intention-Based Motion Control of an Omnidirectional-Type Cane Robot

Abstract: An intelligent cane robot is designed for aiding the elderly and handicapped people's walking. The robot consists of a stick, a group of sensors, and an omnidirectional basis driven by three Swedish wheels. Recognizing the user's walking intention plays an important role in the motion control of our cane robot. To quantitatively describe the user's walking intention, a concept called “intentional direction (ITD)” is proposed. Both the state model and the observation model of ITD are obtained by enumerating the possible walking modes and analyzing the relationship between the human-robot interaction force and the walking intention. From these two models, the user's walking intention can be online inferred using the Kalman filtering technique. Based on the estimated intention, a new admittance motion control scheme is proposed for the cane robot. Walking experiments aided by the cane robot on a flat ground and slope are carried out to validate the proposed control approach. The experimental results show that the user feels more natural and comfortable when our intention-based admittance control is applied.