Details of a Researcher - ISHIGAMI Genya

Papers - ISHIGAMI Genya

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Slip estimation model for traversability-based motion planning of cargo rover on extraterrestrial surface

Nishishita T., Ishigami G.

Frontiers in Robotics and AI 12 2025

ISSN 2296-9144

As part of the robotics technologies required for In-situ resource utilization (ISRU), the development of cargo rovers for transporting resources is needed. However, these cargo rovers have unique technical challenges that differ from conventional exploration rovers, including the need to traverse rough terrains with their varying mass due to transporting payloads. Moreover, research addressing these challenges has been limited, and the relevant technologies have not been fully established. To address these challenges, this paper proposes a parametric model for estimating wheel slippage. The model is formulated as a function of four input parameters: slope angle, rover heading angle, payload mass, and wheel angular velocity, and is applicable to resource-transporting rovers with varying mass. Additionally, the use of a parametric model reduces computational load, which offers advantages for onboard implementation. The proposed estimation model was quantitatively evaluated by comparing datasets obtained from multi-body dynamics analysis. This paper also introduces a new traversability assessment model which incorporates the proposed slip estimation model. We demonstrated the proposed model by integrating it into a sampling based motion planning. The simulation result of the motion planning show that the planner with our model can generate safer motions and enables the rover to reach the target regardless of the cargo payload.

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Snap and Jump: How Elastic Shells Pop Out

Takara Abe, Isamu Hashiguchi, Yukitake Nakahara, Shunsuke Kobayashi, Ryuichi Tarumi, Hidetoshi Takahashi, Genya Ishigami, Tomohiko G. Sano

2024.10

Grip, walk, crawl, and jump. Soft robots are integrated functional structures composed of compliant mechanisms, whose activity spans various industrial applications such as surgery, healthcare, surveillance, and even planetary exploration. One of their promising mobility mechanism is snap-buckling; the instability mode of flexible structures passing from one equilibrium state to another can instantaneously generate large power for its motion. Predicting their performance with even simple geometry requires disentangling material, geometric nonlinearity, and contact, thereby still being a challenging problem to date. Here, we study the jumping dynamics of hemispherical elastic shells driven by snap-buckling, as a model system of soft jumping mechanisms, combining experiments, simulations, and analytical theory. We find that the contact transition dynamics trigger the jumping phenomenon upon snap-buckling by constructing the analytical predictions with shell elasticity in excellent agreement with both experiments and simulations. Despite the simple geometry of the shell, its dynamical performance primarily relies on a complex interplay between elasticity, geometry, and contact friction. By elucidating the dynamics of the building blocks of soft robots that undergo large deformations, we can build their predictive experimental and numerical framework. Our research paves the way for designing soft robots suitable for the required loading conditions or structural requirements without empirical methods.

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Tangle- and Contact-free Path Planning for a Tethered Mobile Robot using Deep Reinforcement Learning

Shimada, R., and Ishigami, G.,

Frontiers in Robotics and AI (Frontiers in Robotics and AI) 11 1388634 (13 pages) 2024.09

Research paper (scientific journal), Joint Work, Lead author, Corresponding author, Accepted, ISSN 2296-9144

This paper presents a tangle- and contact-free path planning (TCFPP) for a mobile robot attached to a base station with a finite-length cable. This type of robot, called a tethered mobile robot, can endure long-time exploration with a continuous power supply and stable communication via its cable. However, the robot faces potential hazards that endanger its operation such as cable snagging on and cable entanglement with obstacles and the robot. To address these challenges, our approach incorporates homotopy-aware path planning into deep reinforcement learning. The proposed reward design in the learning problem penalizes the cable-obstacle and cable-robot contacts and encourages the robot to follow the homotopy-aware path toward a goal. We consider two distinct scenarios for the initial cable configuration: 1) the robot pulls the cable sequentially from the base while heading for the goal, and 2) the robot moves to the goal starting from a state where the cable has already been partially deployed. The proposed method is compared with naive approaches in terms of contact avoidance and path similarity. Simulation results revealed that the robot can successfully find a contact-minimized path under the guidance of the reference path in both scenarios.

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Acoustic Odometry for Wheeled Robots on Loose Sandy Terrain

Andreu Gimenez Bolinches and Genya Ishigami

Proceedings of 13th International Workshop on Robot Motion and Control (RoMoCo2024) 255-260 - 260 2024.07

Research paper (international conference proceedings), Joint Work, Last author, Accepted, ISSN 2575-5579

This work proposes a system capable of estimating the longitudinal velocity of a wheeled robot on loose sandy terrain using only acoustic sensors. These will likely be present anyway in many future ground mobile robots for human-robot interaction purposes. The proposed system consists of an audio feature extraction module, based on gammatone filterbanks, and a prediction module, based on a convolutional neural network. The proposed system has been tested in a single wheel test bed with a wheel driving up to speeds of 0.07 m/s in a wide range of wheel slippage resulting in an average drift of 5 mm/s. A qualitative evaluation of the proposed system against other sources of odometry shows that acoustic and visual methods vulnerabilities do not overlap, which indicates that a system based on acoustic sensors can be a feasible auxiliary source of odometry. The system is able to make a prediction from a single audio frame with a duration of 15 ms in only 2 ms on a user-level commercially available CPU.

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Parameter study and identification of DEM modeling for varied sand moisture content based on bulldozing experiment

Sato N., Ishigami G.

Journal of Terramechanics (Journal of Terramechanics) 113-114 100971 (15 pages) 2024.06

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

The discrete element method (DEM) has been widely used to simulate varied sand particles interacting with earthmoving machines. However, past research using DEM barely addressed accurate verification and validation for different sand moisture content. Therefore, the main purpose of this paper is to reveal the range of key parameters of an adhesive force model used in the DEM simulation corresponding to the specific sand moisture content. We considered the bulldozing phenomenon to be typical earthmoving work and performed the bulldozing experiments under different sand moisture levels to investigate the bulldozing force variations. Subsequently, the DEM simulation with an adhesive force model calculated the bulldozing force corresponding to the experimental results. The values for two adhesive parameters, i.e., a scaling magnitude and the maximum adhesive distance between particles, were adjusted such that the maximum bulldozing force calculated in the DEM coincides with that of the experiments under different moisture contents. The experimental verification of the DEM revealed the relationship curves between these two key parameters corresponding to the different moisture content. The relationship obtained in this paper implies that the DEM simulation carefully adjusting the adhesive force parameters can reproduce machine interaction on moist sand environments accurately.

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BenchNav: Simulation Platform for Benchmarking Off-road Navigation Algorithms with Probabilistic Traversability

Masafumi Endo, Kohei Honda, Genya Ishigami

2024.05

As robotic navigation techniques in perception and planning advance, mobile robots increasingly venture into off-road environments involving complex traversability. However, selecting suitable planning methods remains a challenge due to their algorithmic diversity, as each offers unique benefits. To aid in algorithm design, we introduce BenchNav, an open-source PyTorch-based simulation platform for benchmarking off-road navigation with uncertain traversability. Built upon Gymnasium, BenchNav provides three key features: 1) a data generation pipeline for preparing synthetic natural environments, 2) built-in machine learning models for traversability prediction, and 3) consistent execution of path and motion planning across different algorithms. We show BenchNav's versatility through simulation examples in off-road environments, employing three representative planning algorithms from different domains. https://github.com/masafumiendo/benchnav

Perception-and-Energy-aware Motion Planning for UAV using Learning-based Model under Heteroscedastic Uncertainty

Reiya Takemura and Genya Ishigami

Proceedings of the 2024 IEEE International Conference on Robotics and Automation (ICRA 2024) pp. 10103-10109 - 10109 2024.05

Research paper (international conference proceedings), Joint Work, Last author, Accepted, ISSN 10504729

Global navigation satellite systems (GNSS) denied environments/conditions require unmanned aerial vehicles (UAVs) to energy-efficiently and reliably fly. To this end, this study presents perception-and-energy-aware motion planning for UAVs in GNSS-denied environments. The proposed planner solves the trajectory planning problem by optimizing a cost function consisting of two indices: the total energy consumption of a UAV and the perception quality of light detection and ranging (LiDAR) sensor mounted on the UAV. Before online navigation, a high-fidelity simulator acquires a flight dataset to learn energy consumption for the UAV and heteroscedastic uncertainty associated with LiDAR measurements, both as functions of the horizontal velocity of the UAV. The learned models enable the online planner to estimate energy consumption and perception quality, reducing UAV battery usage and localization errors. Simulation experiments in a photorealistic environment confirm that the proposed planner can address the trade-off between energy efficiency and perception quality under heteroscedastic uncertainty. The open-source code is released at https://gitlab.com/ReI08/perception-energy-planner.

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Accurate Rover Mobility Analysis Using HILS-DRFT with Real-Time Parameter Tuning Approach

Takahiro Fuke, Sora Ishikawa and Genya Ishigami

Proceedings of the 21st International and 12th Asia-Pacific Regional Conference of the International Society for Terrain-Vehicle Systems 2024.01

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

Granular Flow in Reduced Gravity: Analysis and Insights from Centrifuge Experiments at the International Space Station

Takuya Omura and Genya Ishigami

Proceedings of the 21st International and 12th Asia-Pacific Regional Conference of the International Society for Terrain-Vehicle Systems 2024.01

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

DEM-Based Analysis and Optimization of Excavation Bucket Drum for In-Situ Resource Utilization

Tomoyasu Nakano, Takuya Omura and Genya Ishigami

Proceedings of the 21st International and 12th Asia-Pacific Regional Conference of the International Society for Terrain-Vehicle Systems 2024.01

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

Collaborative Robot Systems for Lunar Landing Pad Construction

Kenji Nagaoka, Genya Ishigami, Munetaka Ueno, Keiji Nagatani

Proc. of the AROB-ISBC-SWARM 2024 pp. 985-986 2024.01

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

Task force report on study cycles construction for henceforward International Space Exploration sciences

NAMIKI Noriyuki, ISHIGAMI Genya, SAKURAI Masato, INATOMI Yuko, KOBAYASHI Taizo, TERADA Naoki, MIYAMOTO Hideaki, YAMAGISHI Akihiko, YAMADA Toru

Space Utilization Research, Vol. 38 2023: Proceedings of The Thirty-eighth Space Utilization Symposium (宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS)) 2024.01

CiNii Research

車輪ロボットの移動性能を可視化する可操縦性楕円体の提案

Ryo Ueda, Genya Ishigami

Journal of the Robotics Society of Japan (The Robotics Society of Japan) 2024

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

車輪ロボットの移動性能を可視化する可操縦性楕円体の提案

Yuki Goto, Genya Ishigami

Journal of the Robotics Society of Japan (The Robotics Society of Japan) 2024

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

Modeling of slip rate-dependent traversability for path planning of wheeled mobile robot in sandy terrain

Sakayori G., Ishigami G.

Frontiers in Robotics and AI (Frontiers in Robotics and AI) 11 1320261 (16 pages) 2024

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 2296-9144

Access to Document (DOI)

DEM-based Analysis for Interaction Mechanics of Tracked Vehicle on Soils Containing Water

Yanagawa Hiroki, Ishigami Genya

Journal of the Robotics Society of Japan (The Robotics Society of Japan) 42 ( 4 ) 406 - 409 2024

Research paper (scientific journal), Joint Work, Last author, Accepted, ISSN 02891824

<p>Tracked vehicles has been widely used in unstructured environments such as on uneven/deformable terrains. The mobility of the track unit consisting of interconnected metal plates is the key to enhance the safety of the vehicle. This study focuses on the track and soil interaction, particularly the wetted soil. The Distinct Element Method is applied for analyzing the interaction stress between the track and soil with varied moisture content and slip ratio. The analysis revealed that the significant stress is generated to the leading edge of the track unit and the stress distribution shifts toward the rear region of the track in moist soil. </p>

2919 | Accurate Rover Mobility Analysis Using HILS-DRFT with Real-Time Parameter Tuning Approach

Fuke T., Ishikawa S., Ishigami G.

Proceedings of the 21st International and 12th Asia Pacific Regional Conference of the Istvs 99 - 103 2024

Offroad mobility in extraterrestrial exploration can be significantly degraded by vehicle slippage on soft terrain covered with fine powdery sand known as regolith. Comprehensive design analysis and verification of the rover's mobility have been widely investigated using numerical and experimental approaches. Numerical simulations for the mobility analysis require accurate modeling of the contact forces between the wheel and sand. While several wheel-sand interaction models have been proposed based on the Bekker-Wong-Reece theory, the Dynamic Resistive Force Theory (DRFT) proposed in the early 2020s is a notable approach for its low computational cost and adaptability to quasi-dynamic motion. The scaling factor used in DRFT is the only parameter for representing sand-dependent parameters, and its value needs to be empirically tuned to achieve accurate and reliable mobility analysis. Therefore, the authors have integrated a single-wheel test bed into a closed-loop Hardware-In-the-Loop Simulation (HILS) associated with DRFT. This HILS-DRFT experimentally observes the characteristics of the wheel sinking phenomenon in the wheel test bed, and then, the value of the scaling factor is tuned in real-time by the difference between the observed wheel sinkage and the DRFT simulation. This real-time parameter tuning method accurately reproduces wheel mobility, particularly in its transient states, which were previously unachievable with DRFT alone. The proposed HILS-DRFT with the real-time tuning method will contribute to the efficient and reliable development of rovers.

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9295 | Granular Scaling Laws for Accurate Prediction of Wheel Mobility on Slopes in Low-gravity Environments

Omura T., Ishigami G.

Proceedings of the 21st International and 12th Asia Pacific Regional Conference of the Istvs 310 - 316 2024

Analyzing the mobility of wheeled rovers on loose sand in low-gravity environments remains a significant challenge. Among several experimental techniques, such as parabolic flight and reduced-weight tests, granular scaling laws (GSL) have recently been proposed to predict wheel mobility under low-gravity conditions via earth-gravity tests. Although the GSL accurately predicts wheel mobility on flat terrain in low-gravity environments, its capability to predict wheel mobility on slopes in such environments still needs to be verified. This study developed a GSL and investigated its accuracy in predicting wheel mobility on slopes in low-gravity environments. The discrete element method (DEM) was utilized to test wheel mobility at various slope angles under Earth's gravity. Subsequently, by applying a multiple scaling function, the GSL converted the results from the Earth-gravity tests to predict wheel mobility under lunar gravity. The GSL-based predictions were compared with DEM simulations conducted under lunar gravity conditions. The results indicated that the wheel mobility under lunar gravity predicted by the GSL closely corresponded to that calculated via the DEM. These findings indicate that the GSL can accurately predict wheeled-rover mobility on slopes in low-gravity environments.

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4213 | DEM-Based Analysis and Optimization of an Excavation Bucket Drum for In-Situ Resource Utilization

Nakano T., Omura T., Ishigami G.

Proceedings of the 21st International and 12th Asia Pacific Regional Conference of the Istvs 151 - 157 2024

Lunar infrastructure construction involves leveling of the lunar surface and collecting lunar regolith as a building material. RASSOR 2.0 developed by NASA is one of the typical robotic vehicles as a lunar excavator. It features cylindrical rotating bucket drums for collecting regolith, positioning it as a pivotal tool for future lunar in-situ resource utilization and infrastructure development. However, the optimization of the bucket drum's shape and its motion remain as open issue. Therefore, this study aims to find an optimal design of the bucket drum through numerical simulation using the discrete element method (DEM). We introduce five key design parameters of the bucket drum: two of them are related to the bucket shape (scoop throat length, scoop inlet number) and the rest of them are to motion (bucket vertical force, horizontal velocity, and angular velocity). These five parameters were examined in accordance with two performance indices: the sand fill ratio in the drum and the power consumption of the excavation. Solving the multi-objective problem of increasing the fill ratio and reducing power consumption, we found an optimal bucket drum shape and motion. Subsequently, a bucket drum reflecting the optimal shape was fabricated, and the optimal motion was tested. The test results qualitatively matched with the results derived from the DEM analysis. This outcome highlights the validity of the relationship between the design parameters and two performance indices.

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Granular flow experiment using artificial gravity generator at International Space Station

S. Ozaki, G. Ishigami, M. Otsuki, H. Miyamoto, K. Wada, Y. Watanabe, T. Nishino, H. Kojima, K. Soda, Y. Nakao, M. Sutoh, T. Maeda, T. Kobayashi

npj Microgravity (npj Microgravity) 9 ( 1 ) 61 (13 pages) 2023.12

Research paper (scientific journal), Joint Work, Accepted

Studying the gravity-dependent characteristics of regolith, fine-grained granular media covering extra-terrestrial bodies is essential for the reliable design and analysis of landers and rovers for space exploration. In this study, we propose an experimental approach to examine a granular flow under stable artificial gravity conditions for a long duration generated by a centrifuge at the International Space Station. We also perform a discrete element simulation of the granular flow in both artificial and natural gravity environments. The simulation results verify that the granular flows in artificial and natural gravity are consistent. Further, regression analysis of the experimental results reveals that the mass flow rate of granular flow quantitatively follows a well-known physics-based law with some deviations under low-gravity conditions, implying that the bulk density of the granular media decreases with gravity. This insight also indicates that the bulk density considered in simulation studies of space probes under low-gravity conditions needs to be tuned for their reliable design and analysis.

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