Eijiro Takeuchi

Collaborative mapping of an earthquake-damaged building via ground and aerial robots

We report recent results from field experiments conducted with a team of ground and aerial robots engaged in the collaborative mapping of an earthquake-damaged building. The goal of the experimental exercise is the generation of three-dimensional maps that capture the layout of a multifloor environment. The experiments took place in the top three floors of a structurally compromised building at Tohoku University in Sendai, Japan that was damaged during the 2011 Tohoku earthquake. We provide details of the approach to the collaborative mapping and report results from the experiments in the form of maps generated by the individual robots and as a team. We conclude by discussing observations from the experiments and future research topics.

A 3-D Scan Matching using Improved 3-D Normal Distributions Transform for Mobile Robotic Mapping

A 3D scan matching is an important component for sensor based localization and mapping by a mobile robot in natural environment. In this paper, the present authors propose a way to extend 2D normal distributions transform (NDT) scan matching method to 3D scan matching, and its improvement for faster processing time. This scan matching method divides scan into voxels, and approximates scan points in each cell into normal distribution. That matching time is O(N) with N of the number of input scan points. The authors describe in this paper, NDT for 3D scan points, its acceleration using the dual resolutions of NDT, and experiments of map building in large scale environments

An Open Approach to Autonomous Vehicles

Autonomous vehicles are an emerging application of automotive technology. They can recognize the scene, plan the path, and control the motion by themselves while interacting with drivers. Although they receive considerable attention, components of autonomous vehicles are not accessible to the public but instead are developed as proprietary assets. To facilitate the development of autonomous vehicles, this article introduces an open platform using commodity vehicles and sensors. Specifically, the authors present algorithms, software libraries, and datasets required for scene recognition, path planning, and vehicle control. This open platform allows researchers and developers to study the basis of autonomous vehicles, design new algorithms, and test their performance using the common interface.

Vehicle localization in outdoor woodland environments with sensor fault detection

This paper describes a 2D localization method for a differential drive mobile vehicle on real forested paths. The mobile vehicle is equipped with two rotary encoders, Crossbows NAV420CA inertial measurement unit (IMU) and a NAVCOM SF-2050M GPS receiver (used in StarFire-DGPS dual mode). Loosely-coupled multisensor fusion and sensor fault detection issues are discussed as well. An extended Kalman filter (EKF) is used for sensor fusion estimation where a GPS noise pre-filter is used to avoid introducing biased GPS data (affected by multi-path). Normalized innovation squared (NIS) tests are performed when a GPS measurement is incorporated to reject GPS data outliers and keep the consistency of the filter. Finally, experimental results show the performance of the localization system compared to a previously measured ground truth.

1Km autonomous robot navigation on outdoor pedestrian paths “running the Tsukuba challenge 2007”

This paper presents and describes the approach for achieving long distance autonomous navigation with a mobile robot on outdoor cluttered pedestrian paths. The task was to finish an event launched by the City of Tsukuba in Japan, called ldquoReal World Robot Challengerdquo, of navigating 1km autonomously in a real environment with real pedestrians and bicycles. The hardware, software and strategy for navigating in cluttered environments is explained. Moreover, the complementary functionality of the overall system where map-based and sensor-based navigation seamlessly change, is presented. The robustness of the system is validated with experimental results.

Robotic control vehicle for measuring radiation in Fukushima Daiichi Nuclear Power Plant

The authors developed a robotic control vehicle for measuring the radiation in the Fukushima Daiichi Nuclear Power Plant. There are a lot of hotspots in the nuclear power plant (over several tens mSv/h). Heavy radiation prevents humans from searching and reconstructing it. It is essential to measure the radiation to ensure worker safety. The developed robotic control vehicle can measure radiation using a γ-cam and TALON with a radiation sensor. A heavily shielded operation box was built for reducing the exposure of radiation to 1/3. Two operators control the TALON and the γ-cam from the shielded operation box. Because of its pinhole mechanism, the γ-cam needs to know the distance to the targets. The 3-D light detection and ranging (LIDAR) was built for distance measurement. It has wide measurement range of up to 20m. Using the 3-D LIDAR and the shielded operation box can reduce the exposure during radiation measurement. The use of the developed robotic control vehicle can realize safe radiation measurement.

Multirobot exploration for search and rescue missions: A report on map building in RoboCupRescue 2009

Mobile robots may be able to aid rescue crews in dangerous environments during search and rescue missions after natural or man-made disasters. In 2006, we began a research project to realize mobile robots that can gather information rapidly at the first stage of a disaster. 3D mapping, which can be an important aid for rescue crews in strategizing rescue missions, is one of our important objectives. Some fundamental elements to enable 3D mapping have been developed. We attended RoboCupRescue 2009 to validate our integrated autonomous 3D mapping system. We demonstrated our mapping system using multiple-robots on the RoboCupRescue field. In this paper, we introduce our mapping system and report the results from the RoboCupRescue competition.

Multi sensor map building based on sparse linear equations solver

This paper proposes fast map building algorithm for multiple modal exteroceptive(external) sensors based on trajectory optimization. To realize localization using multiple modal exteroceptive sensors needs consistent environment maps (landmark maps). Multiple sensor SLAM (simultaneous localization and mapping) is one of solutions to build maps consistently. In implementation of SLAM, approximations of sensor model contribute to get speeded up the algorithm. However in several case, these approximations deteriorate quality of the map. This paper proposes fast and accurate map building algorithm using multiple modal sensors based on sparse linear equations solver. This algorithm needs less approximations-but computation speed is fast. In addition, application of measured data from multiple sensors to this algorithm is described.

Robust localization method based on free-space observation model using 3D-map

This paper proposes robust localization method using a free-space observation model with a 3D map for a particle filter. The free-space observation model judges whether the free space of a laser beam of a sensor is appropriate. The observation model realizes highly robust localization in outdoor environments with many unknown obstacles. This paper describes the free-space observation model and the increase in the calculation speed of the observation model. The proposed localization method achieves 1-km localization in outdoor environments with many unknown objects.

Remote vertical exploration by Active Scope Camera into collapsed buildings

Remote robotic explorations for collapsed buildings in a severe disaster are demanded. However, rescue robots cannot approach the rubble due to safety risks. This study proposes a remote vertical exploration system for collapsed buildings with a robotic inspection system hoisted by a crane. An Active Scope Camera (ASC) has many advantages for the vertical exploration such as a light and flexible continuum body to produce distributed driving forces. The purpose of this paper is to confirm the feasibility of the vertical exploration system with the ASC. The vertical explorations have proper problems related to contact and hanging conditions of the scope cable. We developed a new ASC that has a two-step bending mechanism to produce larger head movement in multi-DOF. We also evaluated the performances of the prototype when the contact areas were small. Finally, we conducted a remote vertical exploration experiments at the simulated collapsed building in 6 m height. The robot could explore in six different pathways by changing head directions and running the rubbles within seven trials. The experimental results showed that the proposed system has high potential to get inserted in the deep area in the rubble.