Complementary c ompound set-point c ontrol by combining muscular internal
force feedforward c ontrol and sensory feedback control i ncluding a time delay
Y. Matsutania, K. Taharab, H. Kinoc and H. Ochid
aDepartment of Mechanical and Intelligent Systems Engineering, National Institute of Technology, Kumamoto College, Kumamoto, Japan; bFaculty of Engineering, Department of Mechanical Engineering, Kyushu University, Fukuoka, Japan; cFaculty of Engineering, Department of Intelligent Mechanical Engineering, Fukuoka Institute of Technology, Fukuoka, Japan; dDepartment of Mechanical Engineering, Tokyo University of Science, Yamaguchi, Japan
ABSTRACT
This paper proposes a new set-point control method for a musculoskeletal arm by combining muscular internal force feedforward control with feedback control including a large time delay. The proposed method accomplishes robust and rapid positioning with a relatively small muscular force. In the positioning by the muscular internal force feedforward controller, a large muscular force
is required to achieve good performance. On the other hand, in the positioning by the feedback controller including the large time delay, the system can easily fall into an unstable state. A simple linear combination of these two controllers makes it possible to improve the control performance and to overcome the drawbacks of each controller in a complementary manner. First, a two-link sixmuscle arm model is considered as a musculoskeletal system in this study. Second, the new set-point control method, which consists of the feedforward control signal and the feedback control signal including the time delay, is designed. Third, the stability of the proposed method is investigated using the Lyapunov–Razumikhin method. Finally, the results of numerical simulations and experiments are presented to demonstrate the advantages of the proposed method.
KEYWORDS
Musculoskeletal arm; internal force; feedforward; feedback
Predicting collisions: time-to-contact forecasting b ased on probabilistic
segmentation and system i dentification
Angel J . S anchez-Garciaa,b, Homero V. Rios-Figueroaa, Hugues Garnierc,d, Gustavo Quintana-Carapiae,
Ericka Janet Rechy-Ramireza and Antonio Marin-Hernandeza
aArtificial Intelligence Research Center, University of Veracruz, Xalapa, Mexico; bSchool of Statistics and Informatics, University of Veracruz, Xalapa, Mexico; cUniversity of Lorraine, CRAN, Vandoeuvre-les-Nancy, France; dCNRS, CRAN, UMR 7039, France; eDepartment ELEC, Vrije Universiteit Brussel, Brussels, Belgium
ABSTRACT
The Time-to-contact (TTC) estimate is mainly used in robotics navigation, in order to detect potential danger with obstacles in the environment. A key aspect in a robotic system is to perform its tasks promptly. Several approaches have been proposed to estimate reliable TTC in order to avoid collisions in real-time; nevertheless they are time consuming due to a calculation of scene characteristics in every frame. This paper presents an approach to estimate TTC using monocular vision based on the size change of the obstacles over time (τ); therefore, the robotic system may react promptly to its environment. Our approach collects information from few data of an obstacle, then the behavior of the movement is found through an online recursive modeling process, and finally, a forecasting of the upcoming positions is computed. We segment the obstacles using probabilistic hidden Markov chains. Our proposal is compared to a classical color segmentation approach using two real image sequences, each sequence is composed of 210 frames. Our results show that our proposal obtained smoother segmentations than a traditional color-based approach.
KEYWORDS
Time-to-contact; MAP; system identification; modeling; Forecasting
Quantitative measure for nonlinear unstable systems b ased on t he region of
attraction and its application to designing parameter optimization – inverted
pendulum e xample
T. Horibea, B. Zhoub, S. Haraa and D. Tsubakinoa
aDepartment of Aerospace Engineering, Graduate School of Engineering, Nagoya University, Nagoya, Japan; bDepartment of Mechanical and Aerospace Engineering, University of California Los Angeles, Los Angeles, CA, USA
ABSTRACT
Quantitative stability measures for mechanical systems are highly needed. However, only a few such measures have been proposed for nonlinear systems. In this paper, a quantitative measure of stability for nonlinear systems based on the region of attraction (ROA) is proposed, and the measure is applied to parameter optimization of mechanical systems: multi-link inverted pendulum example. Recently, some techniques for calculating ROAs have been suggested; however, obtaining an accurate estimate of a ROA remains computationally demanding. We illustrate two techniques for efficiently estimating the proposed measure and apply them to the design parameter optimization problem for maximizing the stability measure. A number of simulations show the effectiveness of the proposed method.
KEYWORDS
Design optimization; nonlinear systems; region of attraction; pendubot; multi-link inverted pendulum
The role of computed tomography data in the design of a robotic magneticallyguided endoscopic platform
Peisen Zhanga , Jing Lib, Yang Haoa, Federico Bianchic, Gastone Ciutib,c, Tatsuo Araib,d, Qiang Huanga,b and Paolo Dariob,c
aintelligent Robotics institute, school of Mechatronical engineering, beijing institute oftechnology, beijing, china; bbeijing Advanced innovation center for intelligent Robots and systems, beijing institute oftechnology, beijing, china; cthe bioRobotics institute, scuola superiore sant’Anna, Pisa, italy; dGlobal Alliance Laboratory, the University of electro-communications, tokyo, Japan
ABSTRACT
Seventy cases of computed tomography (CT) data were selected from The Cancer Imaging Archive to aid in the design of a magnetically-guided capsule endoscope platform. According to the distance between the large bowel and the abdomen skin measured on CT images, the supine position showed the advantage in reducing the distance between internal and external magnets; thus, we used the supine position as the detection posture for magnetically-guided capsule colonoscopy. From the selected 70 cases of CT data, we chose 30 supine cases with diffrent waistline lengths to extract the centerline of the large bowel as the motion trajectory of the capsule. We analyzed these trajectories to defie the workspace of the capsule and simulated the motion of the capsule inside the large bowel. The distance between the large bowel and the abdomen surface, which can be
regarded as the minimum distance of the internal and external magnets, was calculated and used as the reference for designing the magnet. Based on the abdomen volume and the workspace of the capsule, we provided a minimum workspace of the external magnet and designed an auxiliary degree of freedom for the manipulator to control the capsule to pass through the large bowel.
KEYWORDS
Magnetically-guided capsule endoscope platform; human computed tomography data; capsule workspace; external magnet workspace
