In this paper, we propose a control method of a mobile robot based on perceiving-acting cycle discussed in ecological psychology. We apply modular neural networks for realizing action control based on the perceiving-acting cycle. In the proposed method, the perceptual system and action system restrict each other. Next, we conduct several experiments using our developed robot. The experimental results show the robot can learn actions based on the perceiving-acting cycle. Finally, we discuss the units of the action and behavior using modular neural networks for the robotic control.
A tendon-driven robot mechanism allows us to control the joint stiffness independantly of the joint torques. Generally, the optimal joint stiffness for desired tasks cannot be found easily. So we adopt a Radial Basis Function Network (RBFN) to describe the trajectory of the stiffness matrix, and modify the parameters using Genetic Algorithm (GA) to find the optimal trajectories. As typical tasks that have impulsive disturbance forces, we choose ball hitting and receiving tasks. The optimal joint stiffness for the hitting task gives the ball the fastest initial speed after the hit, on the other hand, the one for the receiving gives the slowest speed. We use a 2 DOF robotic arm driven with 6 tendons, because we can adjust all of elements of the joint stiffness matrix independently of the joint torques. After modifying conventional GA to fit it for real robot experiments, we make two kinds of experiments given above and show the results.
This paper reports about an interactive humanoid robots, Robovie, that work in a science museum where visitors are supposed to study and grow interests toward science. Each visitor wore an RFID tag, and looked around exhibits in the museum. Robovie has an implemented function for an autonomous interaction as free-play  . Moreover, it obtains its exact position, visitors' positions, and their moving history in the museum from ubiquitous sensor networks, including RFID tag readers, recording cameras and infrared cameras. It performs exhibits-guiding by moving around to several exhibits and explaining these exhibits based on the sensor information, in addition to the freeplay interaction. We compared the effect of the exhibits-guiding and the free-play interaction under three operating conditions. As a result, the free-play interaction and exhibits-guiding contributed to promote visitors' interests for science, while Robovie mostly received higher subjective impression, which is probably due to its novelty.
It is important to identify how much the appearance of a humanoid robot affects human behaviors toward it. We compared participants' impressions of and behaviors toward two real humanoid robots in simple human-robot interaction. These two robots have different appearances but are controlled to perform the same recorded utterances and motions, which are adjusted by using a motion capturing system. We conducted an experiment where 48 human participants participated. In the experiment, participants interacted with the two robots one by one and also with a human as a reference. As a result, we found that the different appearances did not affect the participants' verbal behaviors but did affect their non-verbal behaviors such as distance and delay of response. These differences are explained by two factors, impressions and attributions.
This paper proposes an image based self-localization method of a mobile robot. Images are compressed for each column, and average and standard deviation of pixels in each column are used. Environmental data and observation data which are the compressed image data at registration and observation stage respectively are matched and the position of the robot is obtained. A simple and robust matching method based on a voting process is introduced. Search range for the matching is defined based on the Kalman filtering framework. The compression method is applied to omnidirectional images, and several experiments of self-localization of a mobile robot with omnidirectional images evaluate the proposed methods.
Speeding up of robot motion provides not only improvement in operating efficiency but also dexterous manipulation using unstable state or non-contact state. To produce high-speed manipulation, we have developed a robot system with 1 [kHz] vision sensors. In this paper, a hybrid trajectory generator is proposed so as to get high performance out of high-speed robot system. This algorithm consists of both mechanical high-speed motion and sensor-based reactive motion to target movement. As an example of high-speed manipulation, a robotic batting task have been achieved. In addition, performance evaluation based on manipulator dynamics and system constraint is analyzed.
A planning method for knotting and tightening of deformable linear objects is proposed. Firstly, we briefly explain crossing state description and basic operations corresponding to crossing state transitions. Possible sequences of crossing state transitions, that is, possible manipulation processes can be generated once the initial and the objective states are given. Secondly, a method to determine grasping points and their moving direction is proposed in order to realize derived manipulation processes. Then, it is theoretically found that any knotting manipulation of a linear object placed on a table can be realized by an one-armed robot with three translational DOF and one rotational DOF. Thirdly, a planning method for tying tightly is established to complete a knot because the knot fulfills its fixing function after it is tightened. Finally, it is demonstrated that an one-armed robot system can plan and execute tying and tightening a slipknot.
This paper reports the development of a compact and light-weight personal vehicle called the“Personal riding-type wheeled Mobile Platform (PMP) ”that consists of two wheels and a standing base for a human rider. The two wheels are driven independently, and forward and backward movement and steering are achieved by simply changing the relative position of the rider's center of gravity (COG) on the base. The vehicle has two distinct advantages: a reduction in total weight through its simple structure and a space-saving design that does not use a steering unit. In this paper, we introduce the first prototype (PMP-1) and the second (PMP-2) whose weight is smaller than 12 [kg], and propose its posture stabilizing and running control methods to realize the proper forward and backward movement by changing the position of the rider's COG. In order to achieve steering control according to the rider's intentions, we propose the structure for detecting the rider's COG on the base and the steering control method. We also investigated the steering control method to improve maneuverability in various estimated standing poses. Our experimental results demonstrate that natural steering control can be achieved using the rider's COG based on the rider's intentions.
This paper proposes Message-Oriented NEtworked-robot Architecture, or MONEA, as an efficient development platform architecture for multifunctional robots. In order to avoid problems occurred in multifunctional robot developments, we design the archirecture to fulfill the following three features. Firstly, it embodies the Meta-Architecture for Networked-Robots. Secondly, it supports Bazaar-Style Development Model. Finally, it doesn't require heavy weight middleware. To realize them, we developed an information sharing framework named Networked-Whiteboard Model along with Message passing framework via P2P Virtual Network. A development methodology using Interest-Oriented Module Groups and Software Patterns is also presented as a means to reduce complexity risks. A middleware is developed as an implementation of this architecture, and we verify the availability and effectivity of our platform through the development of dialogue robot for exhibition.
This paper presents a new approach to the design of force control parameters for robotic assembly. Appropriate force control parameters are necessary in order to achieve assembly operations successfully and assure high efficiency of the operations. In practical assembly lines, a cycle time that is the time to perform an operation is required to be reduced. In this paper, a designing method of force control parameters that can reduce a cycle time is proposed and applied to Peg-in-Hole operations. In the method, sub-optimal parameters are obtained through iterative simulations of assembly operations because it is very difficult to calculate a cycle time analytically. First, the proposed method is formulated as an optimization problem. Next, a simulator for robotic Peg-in-Hole operations is developed based on preliminary experiments. Force control parameters are then optimized by using the simulator. Finally, experimental results are shown to demonstrate the validity of the parameters obtained through the proposed method.