Published papers

Our project aims to search for methane-oxidizing microbes on the Mars surface. The project is in preparation under the scheme of the MELOS working group. Martian soil will be sampled from a depth of about 5 - 10 cm below the surface, where organisms are expected to be protected from the harsh hyper-oxidative environment of the Mars surface. The soils will be stained with a cocktail of fluorescent reagents, and examined by fluorescence microscopy. A combination of fluorescent dyes has been selected to identify life forms in samples. A combination of dyes will be used to detect membranes surrounding the "cell". A substrate dye that emits fluorescence upon cleavage by a catalytic reaction will be used to detect the catalytic activity of the "cell". This combination will also be useful for detecting pre-biotic organic material as well as remnants of ancient Martian life. Hydrolysis of the polymers in the "cell" followed by HPLC for amino acid analysis will be effective for examining whether Martian life is identical to or different from terrestrial life. The number and type of the amino acids as well as their chirality will be analyzed to distinguish whether the polymers are contaminants from Earth.

Mobile robot used for planetary exploration performs several scientific missions over long distance travel and needs to have a high degree of autonomous mobility system because the communication delay from the Earth impedes its direct teleoperation. Localization of a mobile robot is of particular importance on the autonomous mobility. Classical localization methods such as wheel/visual odometry have been widely investigated and demonstrated, but they possess a well-known trade-off between computational cost and localization accuracy. This paper proposes an accurate gyro-based odometry method for a wheeled mobile robot in rough terrain. The robot in rough terrain is often subject to large wheel slip or vehicle sideslip related with its steering maneuver, and those slips degrade the localization accuracy. The basic approach of the proposed method is to exploit odometry data for the robot distance traveled as well as gyroscope data for the robot heading calculation; however each data-set is weighted in accordance with steering characteristics of a robot in rough terrain. The usefulness of the proposed method is examined through field experiments using a wheeled mobile robot testbed in Martian analog site. The experimental result confirms that the proposed method accurately estimates the robot trajectory.

Wheeled vehicle mobility on loose sand is highly subject to shear deformation of sand around the wheel because the shear stress generates traction force of the wheel. The main contribution of this paper is to improve a shear stress model for a lightweight wheeled vehicle on dry sand. This work exploits two experimental approaches, an in-wheel sensor and a particle image velocimetry that precisely measure the shear stress and shear deformation generated at the interaction boundary. Further, the paper improves a shear stress model. The model proposed in this paper considers a force chain generated inside the granular media, boundary friction between the wheel surface and sand, and velocity dependency of the friction. The proposed model is experimentally validated, and its usefulness is confirmed through numerical simulation of the wheel traction force. The simulation result confirmed that the proposed model calculated the traction force with an accuracy about 70%, whereas the conventional one overestimated the force, and its accuracy was 13% at the best.

In Japan, the reduction in agricultural work population and increase in abandoned cultivated land are major social issues. To overcome these issues, we have proposed a small agricultural robot that supports the transportation of harvested crops while it follows the user. To move in the furrowed field, ridges and furrows where the robot can move must be detected using robot-mounted sensors and follow the ridge while avoiding the ridges and crop rows. However, when the robot follows the user ahead of it, it has difficulty detecting the ridges because of occlusion by the user. In addition, the robot requires to follow the user and move in and out of furrows of different widths in the farm field. To achieve smooth and safe harvesting support in the field with different width furrows, we propose a method for ridge detection and tracking by measuring the furrow width and interpolation using an RGB-D camera and a method for human-following control while avoiding ridges according to the ridge observation state using fuzzy set theory. To verify the proposed methods, experiments in the farm are carried out.

A Martian rover mission is currently entertained in Japan Aerospace Exploration Agency (JAXA) for launch in 2020s. The primary scopes of this mission are to demonstrate the entry-descent-landing and surface exploration technologies on Mars, to search for signs of live organisms, and to determine when the ocean is lost in the past Martian history. In order to cut down the mission cost and the development risk, the spacecraft is designed as a compact medium-class spacecraft whose total wet mass at Earth departure is approximately 900 kg. The spacecraft system consists of the cruise module and the atmospheric entry module which is subdivided into a forebody and an aftbody aeroshell, a landing module, and a rover, in a typical reference mission design under consideration. The current status of research and development is briefly presented as well.

This study proposes an enhanced Granular Scaling Law (GSL) for accurately predicting wheel mobility on sloped terrain in low-gravity environments. First, wheel driving simulations were conducted using the Discrete Element Method (DEM) with a lunar regolith simulant under Earth's gravity. The GSL was then applied to convert simulation data obtained under various slope angles and wheel angular velocities into corresponding predictions for lunar gravity. These GSL-based predictions were validated against additional DEM simulations conducted directly under lunar gravity. The comparison revealed that the enhanced GSL accurately predicts four key mobility parameters: wheel horizontal velocity, slip ratio, sinkage, and power consumption, with a mean square percentage error of less than 5%. Notably, the study confirmed that GSL remains effective even in transient states and high-speed driving conditions, where wheel-soil interactions become particularly complex. This comprehensive verification, covering slopes up to ±10∘ and slip ratios ranging from negative to approximately 0.9, demonstrates that the enhanced GSL serves as a highly effective predictive method. It provides a practical framework for exploration rover design and mission planning in low-gravity environments, where precise consideration of wheel-soil interactions is critical.

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.

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.

This work aims to establish an energy-efficient strategy for sampling Martian subsurface soil for future extraterrestrial-life exploration missions. To this end, requirements for a robotic arm are carefully examined and an end-effector shape suitable for subsurface soil sampling is determined. A soil tool interaction model is formulated based soil-flow measured by particle image velocimetry (PIV). The proposed model calculates the resistance forces and torque generated during the sampling procedure and is validated through a comparison of experimental data obtained from the force sensor and numerical data calculated from the proposed model. Results indicate that the proposed model provides an accurate estimation of the force generated during soil sampling. Furthermore, the interaction model is capable of estimating the robotic arm's energy consumption and calculating the most efficient tool size to use. (C) 2015 ISTVS. Published by Elsevier Ltd. All rights reserved.

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.

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.