Takayuki Matsuno

Flexible rope manipulation by dual manipulator system using vision sensor

In this paper, we propose a method of the parameter identification of flexible object. We proposed the method to recognize the shape of the rope by using model of the flexible object and visual information. However, in this method, accurate recognition and compensation using the visual information are not possible, when the flexural rigidity of model is greatly different from that of the actual rope. Here, we propose the identification method of the rigidity coefficient of object with experiment results.

Manipulation of Flexible Rope Using Topological Model Based on Sensor Information

There are many deformable objects such as papers, clothes, and ropes in life space of a person. Robots need skills to manipulate deformable objects, in order to take active parts in such space. However, it is difficult for robots to manipulate deformable objects well and possibility of failure to operate deformable objects cannot be denied. Therefore, shape recognition method for deformable object manipulation is required, that has hyper degrees of freedom structures. Thus in this paper, we propose a description method of conditions of ropes using a topological model and knot theory. And, we also propose a recognition method to obtain the structure of rope from sensor information through the CCD cameras when a robot manipulates a rope. The effectiveness of recognition method against a method using three-dimensional data is verified through an experiment

Modeling for Mating Process of Electric Connectors in Robotic Wiring Harness Assembly Systems

Mating a pair of electric connectors is one of the most important steps in a robotic wiring harness assembly system. A piecewise linear force model is reported to describe the successful mating process of connectors via elaborate analysis of force during different phases. The corresponding parameter estimation method of this model is also presented by adapting regular least square estimation methods. A typical type of connectors are investigated in this paper. The results can be extended to other types easily. Experiments show that the presented model has good prospects in fault diagnostic tasks.

Sensor Fusion Based Fuzzy Rules Learning for Humanitarian Mine Detection

In this paper, a sensor fusion based fuzzy rules for humanitarian demining are presented. A fuzzy learning algorithm for extracting fuzzy fusion rules from experimental data of robot-manipulated ground penetrating radar (GPR) and metal detector (MD) is presented. The inputs to the fuzzy learning algorithm are features extracted from both a GPR and an MD while its output is a set of fuzzy rules. Applying the learnt fuzzy fusion rules and knowing GPR and the MD features of a given scan, it is possible to decide if there is a land mine and its approximate depth underground. The features chosen for this fusion algorithm are the peak amplitude of a processed GPR output signal and the peak value of the cumulative sum of amplitudes of MD output signal for the same scanned area. Experimental test results are presented for verifying the validity of the proposed learnt fuzzy fusion rule base

Adaptive sliding mode control for manipulating deformable linear object with input saturation

Manipulating deformable linear objects (DLOs) is much challengeable as the uncertainty resulting from oscillation of DLOs may cause failure in the operation. In this paper, we proposed a position-based control strategy to eliminate the vibration at the end of DLOs. The simplified dynamic model of a DLO is obtained by local linearization, Schur decomposition of matrices and linear transform of variable. Based on the dynamic model, an adaptive law is applied to estimate the uncertain parameters, and a sliding mode controller considering the position constraint condition is designed to force the state variables converging to the equilibrium. The effectiveness of proposed control strategies are verified by numerical simulations.

Strategy of Picking Up Thin Plate by Robot Hand Using Deformation of Soft Fingertip

In this paper, grasping strategy using deformation of soft finger is addressed. Soft fingers, which are made of macromolecular and have large elastic deformation, have gotten a lot of attention. Soft fingers have a peculiarity that high friction force, which stabilizes a grasping condition, is generated by expansion of contact area between tip of soft finger and grasping object. However, until now nobody focuses on the fact that deformation of soft finger enables multi-fingered hand to generate force to manipulate a object which has high aspect ratio and restricted by environment. Accordingly, we focus on a task to pick up a thin plate on a floor using deformation of soft finger. The effectiveness of grasping strategy is confirmed by experiments.

Novel Force Sensor Using Vibrating Piezoelectric Element

We propose a novel tactile sensor, of which sensitivity and sensing range is adjustable. This sensor is a mechanical resonator sensor using a piezoelectric bimorph which measures elastic deformation of media by external force. The sensor is robust and has self-sensing capability. We derived the relationship between sensor output and spring constant at each vibration mode by the piezoelectric analysis and vibration analysis. The validity of sensor was demonstrated by experiment. As an application, a robot fingertip with tactile sensor was fabricated and evaluated.

Skill-based vibration suppression in manipulation of deformable linear objects

Researches on robotic manipulation mainly focus on rigid objects. Whereas, manipulating deformable linear objects (DLOs) such as hoses, wires, cables is common in daily life and many domains such as manufacture, medical surgery and so on. The DLOs are more challengeable to handle, as the uncertainty results from oscillation at the end of DLOs may cause failure in the operation. During manipulating DLOs, especially moving them rapidly, the dynamic characteristics can not be neglected. In this paper, based on the dynamic model of DLOs, we illustrate a skill-based manipulating strategy for eliminating the vibration at the end of DLOs. The method is position-based and inspired from human manipulation skills. From our life experience, when people manipulate DLOs by hand, the oscillation will be significantly reduced if we suddenly lift it up with a certain acceleration. Based on the idea and dynamic model of DLOs, the control strategy by using fuzzy and PI controller is illustrated. The effectiveness of the proposed strategy is confirmed by numerical simulation results. The simulation results show that the proposed method can damp the vibration effectively.

Analytical Design Method of Brachiation Controller on the Irregular Ladder

In this paper, we present the control method to achieve the continuous brachiation on the irregular ladder. The uniform ladder problem was solved by means of symmetric property previously. However, as for the irregular ladder problem, its impossible to build the controller based on symmetric property since the motion cannot be designed symmetrically. Therefore, it is necessary to estimate the energy difference caused by symmetry breaking. We apply passive dynamic autonomous control (PDAC), which was proposed previously, to the locomotion action and evaluate the energy difference. Swing motion is adjusted so as to satisfy the desired energy calculated from the energy difference. The validity of proposed method is tested by the experiment of Gorilla Robot III and the irregular ladder brachiation is realized

Manipulation of deformable linear objects with knot invariant to classify condition

In this paper, we propose a description method of conditions of rope using a topological model and knot theory. And, we also propose a recognition method to obtain the structure of rope from visual information obtained by the CCD cameras when a robot manipulates a rope. There are many deformable objects such as papers, clothes, and ropes in life space of a person. Robots need skills to manipulate deformable objects, in order to take active parts in such space. However, it is difficult for robots to manipulate deformable objects well and possibility of failure to operate deformable objects cannot be denied. Therefore theoretical framework of error recovery for deformable object manipulation is required. For error recovery system, it is necessary to abstract profitable data from deformable objects, which are hyper degrees of freedom structures. Finally, effectiveness of methods are confirmed by experiments