Details of a Researcher - ISHIGAMI Genya

Papers - ISHIGAMI Genya

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Experimental Analysis and Numerical Modeling of Bulldozing Force with Varied Soil Moisture Content

Naohiro Sato, Genya Ishigami

11th Asia-Pacific Regional Conference of the International Society of Terrain Vehicle Systems - 2022

Last author, Accepted

CiNii Research

Development of Underwater Soft Robot Inspired by Flatworm using IPMC and Silicone Rubber

SODA Keinosuke, MATSUHISA Naoji, ISHIGAMI Genya, TAKAHASHI Hidetoshi, FURUSAWA Norihiro, OGAWA Jun

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) (The Japan Society of Mechanical Engineers) 2022 ( 0 ) 2A1-G07 2022

Biomimetic soft robots followed by marine creatures morphology and propulsion mechanics expected to possess high adaptability and maneuverability in underwater world where conventional rigid robots are hardly utilized. Our research group aims to develop an underwater soft robot inspired by marine flatworms which shows a unique and well-organized swimming behavior. Among several types of soft actuators for realizing both robotic softness and flexibility, we focus on an ionic polymer–metal composite (IPMC) as a membranous actuator. This paper mainly introduces a manufacturing process of the IPMC and experimental tests of different types of the IPMC actuators. We found that mean electric resistance of the IPMC increases as decreasing the voltage induced to the IPMC, regardless of the size of the IPMC. The relationship between the voltage and resistance of the IPMC may be correlated with the capacitor component of a simplified RC circuit model of IPMC.

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Development of Underwater Soft Robot Inspired by Flatworm using IPMC and Silicone Rubber

OGAWA Jun, TAKAHASHI Hidetoshi, MATSUHISA Naoji, SODA Keinosuke, FURUSAWA Norihiro, ISHIGAMI Genya

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) (The Japan Society of Mechanical Engineers) 2022 ( 0 ) 2A1-G07 2022

IPMCとシリコーンゴムを用いたヒラムシ型水中ソフトロボットの開発

ロボティクス・メカトロニクス講演会講演概要集 2022

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ヒラムシのひだの羽ばたき位相差を持つ羽ばたき機

ロボティクス・メカトロニクス講演会講演概要集 2022

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Ornithopter with flapping phase difference of flatworm

FURUSAWA Norihiro, SODA Keinosuke, ISHIGAMI Genya, TAKAHASHI Hidetoshi

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) (The Japan Society of Mechanical Engineers) 2022 ( 0 ) 2A1-F10 2022

This paper describes a swimming robot that imitates a flatworm. The model was made with a length of 20 cm, which is about twice the size of a flatworm. As for the folds, they were reproduced by flat wing waves that mimicked the flatworm using a single motor and a phase-shifting slider-crank mechanism. In this way, the phase speed of the folds can be freely changed by changing the phase difference of the crank. The performance of the fabricated robot was evaluated using a high-speed camera and tracking software. For the flapping amplitude, the ornithopter showed no significant errors other than misalignment of parts.

Ornithopter with flapping phase difference of flatworm

FURUSAWA Norihiro, SODA Keinosuke, ISHIGAMI Genya, TAKAHASHI Hidetoshi

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) (The Japan Society of Mechanical Engineers) 2022 ( 0 ) 2A1-F10 2022

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Special issue on Advanced Construction Robot System PREFACE

Ohno, K; Osumi, H; Ishigami, G; Nagatani, K

ADVANCED ROBOTICS 35 ( 23 ) 1375 - 1375 2021.12

ISSN 0169-1864

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CNN-Based Terrain Classification with Moisture Content Using RGB-IR Images

Goto Tomoya, Ishigami Genya

Journal of Robotics and Mechatronics (Fuji Technology Press Ltd.) 33 ( 6 ) 1294 - 1302 2021.12

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 09153942

Unmanned mobile robots in rough terrains are a key technology for achieving smart agriculture and smart construction. The mobility performance of robots highly depends on the moisture content of soil, and past few studies have focused on terrain classification using moisture content. In this study, we demonstrate a convolutional neural network-based terrain classification method using RGB-infrared (IR) images. The method first classifies soil types and then categorizes the moisture content of the terrain. A three-step image preprocessing for RGB-IR images is also integrated into the method that is applicable to an actual environment. An experimental study of the terrain classification confirmed that the proposed method achieved an accuracy of more than 99% in classifying the soil type. Furthermore, the classification accuracy of the moisture content was approximately 69% for pumice and 100% for dark soil. The proposed method can be useful for different scenarios, such as small-scale agriculture with mobile robots, smart agriculture for monitoring the moisture content, and earthworks in small areas.

Simulation Analysis on Steering Characteristics for Vehicle Design of Manned Pressurized Lunar Rover

Naho Yashiro, Genya Ishigami

Proceedings of 20th ISTVS International and 9th Americas Regional Conference (The Japan Society of Mechanical Engineers) 2020 ( 0 ) 002 (11 pages) - B13 2021.09

Research paper (international conference proceedings), Joint Work, Last author, Accepted

This paper describes a steering maneuverability analysis for a manned pressurized lunar rover. To improve steering maneuverability, this paper focused on vehicle design parameters and inputs, such as tread, wheelbase, center of gravity position, and steering angle. The work on this paper first built a simulation model, which used parameters of the moon, and next analyzed cornering characteristics by changing vehicle design parameters. The analysis performed in this paper shows influence of each parameter and input to the motion. Simulation results showed the tread, center of gravity position and steering angle gives impact to steering maneuverability. The paper also discusses and proposes about allowable vehicle design parameters.

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Spatio-temporal prediction of soil deformation in bucket excavation using machine learning

Saku Yuki, Aizawa Masanori, Ooi Takeshi, Ishigami Genya

ADVANCED ROBOTICS (Advanced Robotics) 35 ( 23 ) 1404 - 1417 2021.06

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 0169-1864

This paper proposes a prediction model for three-dimensional spatio-temporal soil deformation in bucket excavation. The prediction model for soil deformation (PMSD) consists of two machine learning processes: the long short-term memory (LSTM) and convolutional autoencoder (Conv-AE). These processes use datasets obtained from an experimental apparatus for bucket excavation developed in this work. The apparatus equips multiple depth cameras that precisely capture time-series data of soil deformation in bucket excavation. The LSTM, an extension of a recurrent neural network, successively predicts three-dimensional soil deformation. The Conv-AE is incorporated to both ends of the LSTM in order to quasi-reversibly compress and reconstruct the datasets so that the computational burden of the LSTM is relaxed. Qualitative and quantitative evaluations of the PMSD confirm the feasibility of time-series prediction of three-dimensional soil deformation. The Conv-AE shows sufficient accuracy equivalent to the measurement accuracy of the depth camera. The prediction accuracy of the PMSD is about 10 mm in most of the cases.

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Visualization and analysis of wheel camber angle effect for slope traversability using an in-wheel camera

Matsumura R, Ishigami G

Journal of Terramechanics (Journal of Terramechanics) 93 1 - 10 2021.02

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 00224898

This paper visualizes and analyzes an effect of a wheel camber angle for the slope traversability in sandy terrain. An in-wheel camera developed in this work captures the wheel-soil contact phenomenon generated beneath the wheel through a transparent section of the wheel surface. The images taken by the camera are then analyzed using the particle image velocimetry. The soil flows with various wheel camber angles are analyzed with regard to the soil failure observed on the slope surface. The analysis reveals that the slope failure and soil accumulation in front of the wheel significantly affect the wheel forces and distributions of the wheel sinkage in the wheel width direction. Further, the side force of the wheel in traversing a slope decreases as the slip ratio increases because the shear stress in the slope downward direction decreases owing to the slope failure.

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Experimental study on wheel-soil interaction mechanics using in-wheel sensor and particle image velocimetry Part I: Analysis and modeling of normal stress of lightweight wheeled vehicles

Tsubaki H, Ishigami G

Journal of Terramechanics (Journal of Terramechanics) 93 23 - 39 2021.02

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 00224898

This study aims to develop a wheel-soil interaction model for a lightweight wheeled vehicle by measuring the normal stress distribution beneath the wheel. The main contribution of this work is to clarify the wheel-soil interaction using a wheel testbed that equips multiple sensory systems. An in-wheel sensor accurately measures the normal stress distribution as well as the contact angles of the wheel. Particle image velocimetry with a standard off-the-shelf camera analyzes soil flow beneath the wheel. The proposed model for the normal stress distribution is formulated based on these experimental data and takes into account the following phenomena for the lightweight vehicles that have not been considered in the classical model: (1) the normal stress distribution takes the form of a Gaussian curve; (2) the normal stress distribution concentrates in the front region of the wheel contact patch; (3) the distribution is divided into two areas with the boundary determined by the maximum normal stress angle; and (4) the maximum normal stress exponentially decreases as the slip ratio increases. Then, the proposed model is experimentally validated. Furthermore, a simulation study for the wheel driving characteristics using the proposed model confirms the accuracy of the proposed model.

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Spatio-Temporal Prediction of Soil Deformation using Machine Learning

Saku Yuki, Aizawa Masanori, Ooi Takeshi, Ishigami Genya

Journal of the Robotics Society of Japan (The Robotics Society of Japan) 39 ( 4 ) 367 - 370 2021

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 0289-1824

Unmanned construction machine working in dangerous environments such as construction sites and disaster areas has been developed. However, it is still necessary to improve its work efficiency especially during bulldozing and excavating soil. This research aims to develop a method for predicting soil deformation using machine learning. The feasibility of the proposed method is verified in a scenario where a simple bulldozing blade excavates soil. In the experiment, soil deformation at a front part of the blade is captured by multiple stereoscopic cameras. The camera provides depth data that are then converted to height field data. This dataset is fed to machine learning using Recurrent Neural Network (RNN) because soil deformation is continuous phenomena depending on time variation. The learned model for predicting soil deformation is confirmed in varied intrusion depth of the bulldozing blade.

Energy-aware trajectory planning for planetary rovers

Sakayori G, Ishigami G

Advanced Robotics (Advanced Robotics) 35 ( 21-22 ) 1302 - 1316 2021

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 01691864

Planetary rovers are becoming indispensable for exploration activities and science missions. The rover used in such mission is often limited in its operation time owing to power and computational resources of the rover. In this paper, a trajectory planning method for a planetary rover is proposed that considers vehicle dynamics, and energy management of the rover. The vehicle dynamics is approximated from a dynamic simulation of the rover, which can estimate the power consumption in accordance with terrain traversability of the rover. The power generation of the solar array panel mounted on the rover is also taken into account. The simulation study confirmed the usefulness of the proposed method, especially in scenarios where slopes could be observed, and one result indicated that the energy margin could be improved by 4.1 kJ, 13.9 (Formula presented.) at maximum.

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EXPERIMENTAL MEASUREMENT OF SOIL-TRACK CONTACT STRESS IN STEERING MOTION ON LOOSE SAND

Shomura T., Ishibashi S., Ishigami G.

Proceedings of the 20th International and 9th Americas Conference of the International Society for Terrain-Vehicle Systems, ISTVS 2021 (Proceedings of the 20th International and 9th Americas Conference of the International Society for Terrain-Vehicle Systems, ISTVS 2021) 2021

Research paper (international conference proceedings), Joint Work, Last author, Accepted

Modeling the dynamic interaction of construction machines on loose terrain is essential for accurately predicting the vehicle's motion and for reliably conducting its operation. The track system is often exploited as the mobility for the construction machine the track shows high trafficability on loose terrain. Track-terrain interaction mechanics has been well investigated in the past, while that in steering motion of the track remains an open issue. Therefore, this research aims to clarify the interaction mechanics of the steering track on loose sand using the following experimental apparatus: an in-track sensor and a track-steering testbed. The in-track sensor possesses multiple small three-axis sensors on the track shoes. Each track shoe has multiple holes for the sensor such that the sensing position is selectable along with the track direction. This in-track sensor can measure the contact stress distribution generated between the track and loose sand. The steering testbed emulates a pivot turning of a tracked vehicle by offsetting the track at an arbitrary distance from the center of rotation of the steering testbed. The experiments using these two apparatuses reveal that the shear stress beneath the track shows a different tendency in its steering motion: the maximum shear stress of the towed track is generated at the center of the contact region while that of the driving track is at the front region. These observations can contribute to a better understanding of the steering motion of a construction machine on loose terrain.

Wide-range routing method for lunar exploration rovers using multi-objective optimization

Reina Nakanishi, Genya Ishigami

Advanced Robotics (Robotics Society of Japan) 35 ( 21-22 ) 1317 - 1331 2021

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 01691864

This paper presents a wide-range routing method for multiple rovers deployed for a lunar polar exploration mission. In the mission scenario considered in this paper, multiple exploration points are divided into several sets of points to be assigned to multiple rovers. Subsequently, routes between the exploration points are generated for each rover. This assignment and routing problems are well known as the multiple Traveling Salesman Problem (mTSP). The scenario aims to minimize two objective functions: the sum and standard deviation of operation time among the multiple rovers. This problem is then subject to the multi-objective mTSP (MOmTSP). Therefore, the proposed method is composed of a three-step procedure for solving the MOmTSP. First, the k-means algorithm divides an exploration area into several regions for the number of rovers. Subsequently, a routing algorithm with the space-filling curve and 2-opt algorithm determines the order of exploration points in each region. A local path planner then generates a feasible path between two exploration points. The simulation results using the proposed method with 80 cases are statistically analyzed. We confirm that the proposed method solves the multiple optimization problems by finding the routes that can equalize the rover's operation time and minimize their deviations.

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Traversability-based Trajectory Planning with Quasi-Dynamic Vehicle Model in Loose Soil

Takemura R., Ishigami G.

Proceedings of the 2021 IEEE International Conference on Intelligent Robots and Systems (IEEE International Conference on Intelligent Robots and Systems) 8411 - 8417 2021

Research paper (international conference proceedings), Joint Work, Last author, Accepted, ISSN 21530858

This paper presents a framework for trajectory planning that explicitly considers robotic traversability based on a quasi-dynamic vehicle model of a mobile robot in loose soil. The quasi-dynamic model estimates the slip effect due to wheel-terrain interaction forces regardless of solving complicated multibody dynamics. Therefore, our proposed model is computationally efficient for quantifying how the robot safely traverses each trajectory segment generated by a planning algorithm. The trajectory planning in our framework exploits a sampling-based incremental search algorithm, i.e., Closed-Loop Rapidly-Exploring Random Trees (CL-RRT). In the tree extension process of the CL-RRT, the traversability assessment based on the quasi-dynamic vehicle model excludes the trajectory segment associated with a hazardous wheel slip ratio. As a result, a trajectory generated from the proposed framework is safely traversable for the robot even in high slip terrain. Simulation results show that the proposed vehicle model can run 57K times faster than the dynamic model and predict the robot motion 3 times more accurately than the kinematic model. Multiple trials of the trajectory planning simulation show that our proposed framework incorporated with the quasi-dynamic model reduces a wheel slip ratio by about 40 % as compared with the kinematic model.

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TOWARDS MODIFIED DYNAMIC RESISTIVE FORCE THEORY FOR A FAST-ROTATING WHEEL ON LOOSE SAND

Tanabe Y., Ishigami G.

Research paper (international conference proceedings), Joint Work, Last author, Accepted

Newly proposed missions to the Moon/Mars often require vehicles to operate at high speed for time-efficient surface explorations. Among wheel-terrain interaction models in the past being applicable for quasi-static locomotion, a granular Resistive Force Theory (RFT) is increasingly employed alternatively for its simplicity and applicability. The RFT has also been extended to the Dynamic RFT (DRFT), which considers the rate-dependent effects often seen in the high-speed locomotion. In this research, first, we validate the DRFT through single-wheel experiments. The results suggest that the original DRFT underestimates the influence of wheel rut and that the granular flow beneath the wheel may decrease the wheel traction force. We then propose an empirically modified DRFT (m-DRFT), which considers an appropriate evaluation of the wheel rut depth and a simplified model for the granular flow. The comparison with the experimental results confirms that the m-DRFT accurately predicts the wheel drawbar pull in relatively low slip conditions while the original DRFT overestimates it. Moreover, the m-DRFT reproduces the temporal oscillations of the drawbar pull generated by the wheel grousers. These results imply that the m-DRFT is applicable for transient locomotion state or even fast-rotating wheel where estimating the sequential changes of wheel forces becomes essential.

TOWARDS HIGH-FIDELITY ANALYSIS ON WHEELED MOBILE ROBOT ON SOFT TERRAIN USING HARDWARE-IN-THE-LOOP SIMULATOR

Ishikawa S., Ishigami G.

Research paper (international conference proceedings), Joint Work, Last author, Accepted

This paper introduces a Hardware-In-the-Loop Simulation (HILS) framework for a wheeled mobile robot traveling on sandy terrain. The HILS is a hybrid method that incorporates an experimental approach into a numerical simulation. The HILS in our work employs a single-wheel testbed for the experimental setup where the traction force of the wheel on soft soil under various slip conditions is measured. The dynamics of the robot vehicle in response to the wheel traction force is calculated by a simple dynamics model based on Newton’s equation of motion. A key technique of the HILS developed in this work is the damping coefficient implemented in the dynamics model. To verify the fidelity and stability of the HILS, wheel driving tests with the HILS are conducted in the following process: first, a wheel driving data (wheel translational velocity, wheel traction force, and wheel slip) with various input parameters (damping coefficient and wheel angular velocity) is experimentally measured only using the wheel testbed. Subsequently, another wheel driving data is measured while the HILS calculates the dynamic response of the wheel in accordance with the corresponding external forces. The validity of the HILS is compared based on the difference between the actual and calculated wheel driving data. In this process, the value of the damping coefficient is determined such that the dynamic response well matches with the actual driving data. Furthermore, wheel driving data with external disturbances to the wheel is experimentally simulated using the HILS.

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