Kei Okada

Plane segment finder: algorithm, implementation and applications

This paper describes the development of a plane segment finder, which is able to detect three-dimensional planar surfaces from input images in real-time. We propose an algorithm for detecting plane segments, that includes: 1) plane segment candidate extraction using the 3D Hough transform from depth map information; and 2) fitting the plane segment candidates to the depth map in order to detect the partial plane segment, since the extracted plane segment candidates are general planes, with no boundary. To achieve real-time plane segment finding system, we apply: 1) the recursive correlation method for depth map generation; and 2) the randomized Hough transform for plane segment extraction. Finally, experimental results using an implementation of our system along with a humanoid robot are shown.

Humanoid motion generation system on HRP2-JSK for daily life environment

This paper describes software system for a humanoid robot viewed from a motion generation aspect by taking kitchen helping behaviors as an example of a real world task. Our software consists of high level reasoning modules including 3D geometric model based action/motion planner and runtime modules contains 3D visual processor, force manipulation controller and walking controller. We discuss how a high level motion and action planner based motion generation functions contribute to various real world humanoid tasks and a role of perception based motion generation using a vision sensor and force sensors.

Home-Assistant Robot for an Aging Society

Many countries around the world face three major issues associated with their aging societies: a declining population, an increasing proportion of seniors, and an increasing number of single-person households. To explore assistive technologies that can help solve the problems faced by aging societies, we have tested several information and robot technologies. This paper introduces research on a home-assistant robot, which improves the ease and productivity of home activities. For people who work hard outside the home, the assistant robot performs chores in their home environment while they are away. A case study of a life-sized robot with a humanlike functional body performing daily chores is presented. An integrated software system incorporating modeling, recognition, and manipulation skills, as well as a motion generation approach based on the software system, is explained. Moreover, because housekeepers perform chores one after another in their daily environment, we also aim to develop a system for continuously performing a series of tasks by including failure detection and recovery.

Online decision of foot placement using singular LQ preview regulation

In this paper, we introduce an online decision method of foot placement for legged robots that manages unknown external forces. It consists of a fast trajectory generation method and an optimization method of foot placement. The fast trajectory generation method is based on an explicit solution for singular LQ preview regulation problem of an inverted pendulum model. By using the regulator problem, the conditions of target ZMP trajectory that will not make the COM trajectory diverge and a fast generation method of the COM trajectory which satisfies the target ZMP trajectory are obtained. An online optimization of foot placement is realized by using the fast trajectory generation method. An experiment of the online decision method of foot placement that manages unknown external force shows the performance of the proposed method.

Vision based behavior verification system of humanoid robot for daily environment tasks

This paper describes integrated/intelligent humanoid robot system for daily-life environment tasks. We have realized complex behaviors of a humanoid robot in daily-life environment based on motion planner technique using an environment and manipulation knowledge. However in order to adapt to unknown or dynamic situations, sensor based behavior variation is essentially important. In this paper, we present a design and implementation of sensor based behavior verification system using an environment and manipulation knowledge, which is also used in manipulation motion planner. We also present software architecture that allows us to write a single stream code to perform complex concurrent humanoid motions. By using this architecture, sensor based verification functions are easily integrated in motion generation functions. Finally, we demonstrated a water-pouring task and a dishwashing task of the life-sized humanoid robot HRP2-JSK in a real environment while verifying its own motion

Design of high torque and high speed leg module for high power humanoid

The high power ability of humanoid is desired for application of nursing or running or jumping motions. Achievement of the actuator of light and powerful equivalent to humans is required. In this paper, we propose a method to extract inherent performance from motors by an active temperature control. The method safely improves the output of motors. The active temperature control is achieved by combining the estimation of an internal temperature of the motor with the forced cooling by liquid. We also developed high power motor drivers for the proposed method. An experiment of a high power joint test bench is shown. In this paper, we show a high power prototype biped robot for application of nursing, running or jumping motions. High power actuator system and robust internal body network are developed for high power robot. Basic demonstration experiments of high power motion are shown.

Environment manipulation planner for humanoid robots using task graph that generates action sequence

In this paper, we describe a planner for a humanoid robot that is capable of finding a path in an environment with movable objects, whereas previous motion planner only deals with an environment with fixed objects. We address an environment manipulation problem for a humanoid robot that finds a walking path from the given start location to the goal location while displacing obstructing objects on the walking path. This problem requires more complex configuration space than previous researches using a mobile robot especially in a manipulation phase, since a humanoid robot has many degrees of freedom in its arm than a forklift type robot. Our approach is to build environment manipulation task graph that decompose the given task into subtasks which are solved using navigation path planner or whole body motion planner. We also propose a standing location search and a displacing obstacle location search for connecting subtasks. Efficient method to solve manipulation planning that relies on whole body inverse kinematics and motion planning technology is also shown. Finally, we show experimental results in an environment with movable objects such as chairs and trash boxes. The planner finds an action sequence consists of walking paths and manipulating obstructing objects to walk from the start position to the goal position.

Multi-cue 3D object recognition in knowledge-based vision-guided humanoid robot system

A vision based object recognition subsystem on knowledge-based humanoid robot system is presented. Humanoid robot system for real world service application must integrate an object recognition subsystem and a motion planning subsystem in both mobility and manipulation tasks. These requirements involve the vision system capable of self-localization for navigation tasks and object recognition for manipulation tasks, while communicating with the motion planning subsystem. In this paper, we describe a design and implementation of knowledge based visual 3D object recognition system with multi-cue integration using particle filter technique. The particle filter provides very robust object recognition performance and knowledge based approach enables robot to perform both object localization and self localization with movable/fixed information. Since this object recognition subsystem share knowledge with a motion planning subsystem, we are able to generate vision-guided humanoid behaviors without considering visual processing functions. Finally, in order to demonstrate the generality of the system, we demonstrated several vision-based humanoid behavior experiments in a daily life environment.

Humanoid arm motion planning using stereo vision and RRT search

This paper describes an experimental stereo vision based motion planning system for humanoid robots. The goal is to automatically generate arm trajectories that avoid obstacles in unknown environments from high-level task commands. Our system consists of three components: 1) environment sensing using stereo vision with disparity map generation and on-line consistency checking, 2) probabilistic mesh modeling in order to accumulate continuous vision input, and 3) motion planning for the robot arm using RRTs (rapidly exploring random trees). We demonstrate results from experiments using an implementation designed for the humanoid robot H7.

Vision-based 2.5D terrain modeling for humanoid locomotion

We present an integrated humanoid locomotion and online terrain modeling system using stereo vision. From a 3D depth map, a 2.5D probabilistic description of the nearby terrain is generated. The depth map is calculated from a pair of stereo camera images, correlation-based localization is performed, and candidate planar walking surfaces are extracted. The results are used to update a probabilistic map of the terrain, which is input to an online footstep planning system. Experimental results are shown using the humanoid robot H7, which was designed as a research platform for intelligent humanoid robotics.