In January 2024, a Japanese lunar lander successfully touched down on the moon as part of the Smart Lander for Investigating Moon (SLIM) mission. Accompanying the SLIM on its journey were two small rovers named lunar excursion vehicles (LEV-1 and 2). LEV-2, a transformable nano rover, was particularly designed to capture images of the SLIM on the lunar surface. During the mission, LEV-2 successfully maneuvered and captured images of the lander. Understanding the mobility characteristics of LEV-2 was crucial for the success of this task. This study analyzed the mobility characteristics of LEV-2 through numerical simulation and traveling tests. In the numerical simulation, a dynamics model of LEV-2 was first developed. Subsequently, the motion behaviors of LEV2 were analyzed by utilizing the discrete element method. Traveling tests were then conducted using the LEV-2 engineering model on various terrains covered with a lunar regolith simulant. The results of both the numerical simulations and experiments revealed consistent trends across different moving modes of LEV-2. Furthermore, the simulation results indicated no significant deterioration in the mobility performance of LEV-2 on the moon when compared to that on the Earth. Based on the characteristics predicted from the simulation and the quantitative data obtained from the experiments, it was concluded that LEV-2 is supposed to travel at least 15◦slopes on the moon.

This paper presents a novel approach to sampling subsurface asteroidal regolith under severe time constraints. Sampling operations that must be completed within a few hours require techniques that can manage subsurface obstructions that may be encountered. The large uncertainties due to our lack of knowledge of regolith properties also make sampling difficult. To aid in managing these challenges, machine learning-based detection methods using tactile feedback can detect the presence of rocks deeper than the length of the probe, ensuring reliable sampling in unobstructed areas. In addition, given the variability of soil hardness and the short time available, a corer shooting mechanism has been developed that uses a special shape-memory alloy to collect regolith in about a minute. Experiments on subsurface obstacle detection and shooting-corer ejection tests were conducted to demonstrate the functionality of this approach.

Unmanned rescue, observation, and/or research vehicles with high terrain adaptability, high speed, and high reliability are needed in difficult-to-reach locations. However, for most vehicles, high performance over rough terrain reduces the travel speed and/or requires complex mechanisms. We have developed a blade-type crawler robot with a very simple and reliable mechanism, which traverses uneven terrain at high speed. Moreover, the gyro wheel design stabilizes the success of this approach in improving the motion, ensuring robust traversal. The improvement in traveling speed and robustness over uneven terrain by our approach was confirmed by experiment.

Sub-seafloor exploration is an important area of biological and geological research, and often requires samples of seafloor mud to be recovered. The minerals and marine sediments trapped in this mud are also potentially valuable resources. However, seabed exploration has been limited by the complexity and cost of the traditional equipment used. Wide area exploration can be made possible by deploying multiple robots to autonomously search beneath the ocean floor. In this study, we prototyped a sub-seafloor excavation robot for use in seabed exploration. The key system comprised a propulsion unit and an excavation unit that allow the robot to move freely within the seabed. We experimentally demonstrated the ability of the excavation robot to produce curved boreholes with a diameter of 160 mm, a turning radius of 1.67 m, and a depth of 613 mm. Our experimental results confirm that nonlinear excavation is possible using the excavation robot developed.

We investigate brachiating motion dynamics and control of space robot using handrails on in-orbit structures in order to inspect, repair and/or construct them. We deal with one arm type space robot based on the Reconfigurable Brachiating space Robot (RBR). We conduct a micro-gravity flight experiment of the RBR, and we identify kinematical and dynamical parameters of the robot arm. Then, we conduct numerical simulations of 6 DOF robot arm dynamics under the constraint within a two-dimensional plane. It is assumed that the robot arm moves on a large space structure using handrails attached to the structure. When the handrail slowly vibrates due to flexibility of the large structure, then the robot behavior is influenced by its fluctuation. In this paper, we show the simulation results of brachiating motion and discuss the flexibility effects to the robot motion.