Shunsuke Kudoh

A Feedback Controller for Biped Humanoids that Can Counteract Large Perturbations During Gait

In this paper, we propose a new method for biped humanoids to compensate for large amounts of angular momentum induced by strong external perturbations applied to the body during gait motion. Such angular momentum can easily cause the humanoid to fall down onto the ground. We use an Angular Momentum inducing inverted Pendulum Model (AMPM), which is an enhanced version of the 3D linear inverted pendulum model to model the robot dynamics. Because the AMPM allows us to explicitly calculate the angular momentum generated by the ground reaction force, it is possible to calculate a counteracting motion that compensates for the angular momentum generated by external perturbations in real-time.

The dynamic postural adjustment with the quadratic programming method

The postural balance system is one of the most fundamental functions for humanoid robot control. In this paper, we propose a new feedback balance control system for the human body. This system can manipulate large perturbations. It finds the optimal motion for maintaining balance in the 3D space without receiving any feed-forward input beforehand. Two different strategies are adopted for the optimization: the quadratic programming method and the PD control. Simulation results are compared with real human motion; many common features such as rotating arms are observed.

C/sup 2/ continuous gait-pattern generation for biped robots

In this paper, we propose a new method to generate C/sup 2/ continuous gait motion for biped robots. The method is based on the enhanced inverted pendulum mode, which can easily handle angular momentum around the center of gravity. Using our method, it is possible to plan motion paths for biped robots without discontinuity in the acceleration even during switching from single support phase to double support phase, and vice versa.

Humanoid robot motion generation with sequential physical constraints

This paper presents a method to optimize and filter trajectories generated from recorded human motion for a humanoid robot with physical limits. The objective function is responsible for mimicking human trainers, enhancing the possibility for fast convergence, while constraints are used to transform motion within the limit of the capabilities of the humanoid robot. Those constraints for angle, velocity, and dynamic force are represented as B-spline coefficients. An iterative soft-constraint paradigm is proposed to enhance the quality of velocity and force constraints. Collision avoidance is also considered as a constraint. For precision refinement, in regions of high-frequency motion not adequately modeled by an initial splining, B-spline is extensible into a hierarchy so that optimization that meets global criteria can be performed locally. Furthermore, all of the constraints can be used solely as filtering. To use these filters, an effective method to directly decompose a trajectory to a B-spline is also presented

Stepping motion for a human-like character to maintain balance against large perturbations

We propose a method of maintaining balance for a human-like character against large perturbations. The method enables a human-like model to maintain its balance with active whole-body motion, such as rotating its arms, bending down, and taking a step, if necessary. First, we capture the human motions of maintaining balance and abstract essential mechanisms from these motions. Next, we construct a model of maintaining balance that has a simple structure, such as an inverted pendulum. This model has two modes of maintaining balance: keeping the feet on the ground, and stepping. In this paper, the stepping mode is mainly described. Finally, we generate whole-body motion based on the model against several perturbations, and we discuss the validity of our method

Painting robot with multi-fingered hands and stereo vision

In this paper, we describe a painting robot with multi-fingered hands and stereo vision. The goal of this study is for the robot to reproduce the whole procedure involved in human painting. A painting action is divided into three phases: obtaining a 3D model, composing a picture model, and painting by a robot. In this system, various feedback techniques including computer vision and force sensors are used. As experiments, an apple and a human silhouette are painted on a canvas using this system

An inverse kinematics method for 3D figures with motion data

We present a new inverse kinematics method that utilizes the motion data for realtime control and editing. The key idea is to extract parameters necessary for inverse kinematics from the motion data. These parameters are the weight matrix, which determines the motion of the redundant joints, and the transformation functions that define the motion of the end effectors. The user can control the motion by dragging a body segment using a mouse, and the method calculates the new motion using the precomputed parameters. The method enables interactive editing, warping, and retargeting character motions.

Generation of humanoid robot motions with physical constraints using hierarchical B-spline

From recorded human motion, trajectory optimization of a humanoid robot with physical limits being the key constraint is presented. The optimizations objective function preserves the salient characteristics of the original motion, while constraints are used to transform the motion to the limit of the capabilities of the humanoid robot. It is shown that using constraints to limit generated trajectories to physically realizable motion ensures that limits are being met more precisely than by reducing them using a standard objective function. The use of wavelets vs. B-spline is compared, and it is shown that B-spline data representation has pronounced advantages. Furthermore, in regions of high-frequency motion not adequately modeled by an initial splining, B-spline is extensible into a hierarchy so that optimizations can be performed locally which still meet global criteria. It is shown how to use B-spline coefficients in angle-, velocity-, acceleration-, and dynamic force-constraints. To detect trajectory subsections with excessive error in need of control point adjustment and local re-optimization, not only is a traditional error detector used, but also a B-spline density detector is also presented. Generated motions were tested using our simulation program and the robot HRP-2.

Development of an Intelligent Senior-Car in a Pedestrian Walkway

Abstract This research aims at development of a stable mobile robot (personal mobility robot) that can navigate automatically on sidewalks where ordinary citizens are coming and going. Many studies have investigated automated vehicles that move on public roads. In the case of a road environment, many infrastructures and traffic regulations exist. In contrast, in a sidewalk environment, human and robots cross the same area without clear rules. For these reasons, some paths or landmarks are often blocked by unknown obstacles such as bicycles and passing pedestrians. Therefore, the most important requirements for a mobile robot are robust localization and safe navigation without collisions. We proposed simple and novel algorithms for localization using a grid map and navigation for four-wheeled robots. We also developed an intelligent robotic cart (senior car) that moves autonomously along a given course to help people transfer luggage or themselves. The sensors used in this system are three small laser scanners and an optical fiber gyroscope. The robot estimates its global position by using the integrated sensor information and generates local paths for avoiding nearby obstacles. This article describes the structure of the developed senior car and details of the proposed algorithms. We also describe a field experiment of our system in the Tsukuba Challenge 2010. Our robot successfully and autonomously ran the 1.1 km course in a realistic environment. The experiment showed the robot could estimate its position and follow the specified path effectively.

Temporal scaling of upper body motion for Sound feedback system of a dancing humanoid robot

This paper proposes a method to model the modification of upper body motion of dance performance based on the speed of played music. When we observed structured dance motion performed at a normal music playback speed and motion performed at a faster music playback speed, we found that the detail of each motion is slightly different while the whole of the dance motion is similar in both cases. This phenomenon is derived from the fact that dancers omit the details and perform the essential part of the dance in order to follow the faster speed of the music. To clarify this phenomenon, we analyzed the motion differences in the frequency domain, and obtained two insights on the omission of motion details: (1) High frequency components are gradually attenuated depending on the musical speed, and (2) important stop motions are preserved even when high frequency components are attenuated. Based on these insights, we modeled our motion modification considering musical speed and joint limitations that a humanoid robot has. We show the effectiveness of our method via some applications for humanoid robot motion generation.