論文

A high-fidelity simulator for a construction machine particularly contributes to an unmanned construction system since the simulator efficiently manages and schedules tasks required for the machines in a systematic way. Besides, the simulator also provides a virtual reality as a training platform for an operator for tele-operated unmanned construction machine. The simulator is generally subject to a well-known trade-off between computational burden and simulation accuracy. Therefore, the main scope of this research is to establish an accurate and computationally efficient simulator for an excavator, and particularly this paper focuses on an interaction model of an excavator bucket. An accurate excavation mechanics is of a key issue to characterize dynamic motion of the excavator. The model developed in this paper basically exploits the Resistive Force Theory with considering soil surcharge while excavating. The proposed model is experimentally validated in different types of excavation motion using a bucket experimental apparatus.

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.

The safety of lunar and planetary exploration is contingent upon a preliminary assessment of the interaction between loose soils composed of regolith that covers a celestial surface and the landing gear of spacecraft, which should be designed in accordance with the findings of the assessment. However, given the issues associated with replicating the surface layer of celestial bodies on Earth, the verification of the gear design can be challenging. Conducting a real-size low-gravity test in the design verification process of a large spacecraft remains cumbersome and resource intensive. As such, drawing valuable knowledge from scale model tests is the only available solution. This paper presents the results and findings of a dynamic penetration test conducted on a scaled landing pad under microgravity using a drop tower. The experimental findings demonstrate that the results of the dynamic penetration of the pad into the regolith simulant are not necessarily indicative of the worst-case scenario of low-gravity conditions and that they are equivalent to the results obtained in the gravitational environment of the earth. This finding suggests that design verification may be feasible through tests using a full-scale spacecraft model.

We have investigated the element specific magnetic characteristics of single-crystal FeCr2S4 using x-ray absorption spectroscopy (XAS) and x-ray magnetic circular dichroism (XMCD). We have found that the Fe L2,3-edge XAS spectra do not exhibit clear multiplet structures, indicating strong hybridization between the Fe 3d and S 3p orbitals, leading to delocalized rather than localized electronic states. The Fe 3d and Cr 3d spin moments are antiferromagnetically coupled, consistent with the Goodenough-Kanamori rule. The orbital magnetic moments of Fe and Cr are determined to be -0.23 and -0.017 μB/ion, respectively. The large orbital magnetic moment of Fe is due to the d6 configuration under the relatively weak tetrahedra crystal field at the Fe site, and the delocalized Fe electrons maintain the orbital degree of freedom in spite of their itinerant nature. To understand phenomena such as the gigantic Kerr rotation, it is essential to consider not only the orbital degrees of freedom but also the role of spin-orbit coupling, which induces a finite orbital magnetic moment through t2 and e level hybridization under the tetrahedral crystal field. This finite orbital moment serves as a direct indicator of spin-orbit interaction strength and links element-specific orbital magnetism to the large Kerr rotation. On the other hand, the octahedral crystal-field splitting of the Cr 3d level is large enough to result in the quenching of the orbital moment of the Cr ion in FeCr2S4.

Accurate torque prediction for excavating drums is critical for the design and autonomous control of planetary rovers operating in loose, unstructured regolith. Existing terramechanics models may fail to capture the full dynamics of rotating excavation drums. In this paper, we present a unified, physics-based torque prediction model with two novel dynamic effects: a longitudinal, velocity-sensitive bulldozing resistance term that grows logarithmically with forward speed, and a regolith-accumulation torque that evolves as the drum buckets fill. We validate our approach on a custom four-wheel holonomic rover excavating Silica Sand No. 5 across multiple test sequences spanning different angular and translational velocities. The model achieves a normalized RMSE generally below 12%, an MAE under 0.15 Nm, and (Formula presented.), in nearly all cases, accurately reproducing the temporal evolution toward steady-state torque plateaus. Its modular structure and reliance on minimal empirical tuning make it suitable for real-time torque estimation in future autonomous planetary missions.

Four-wheel independent drive and steering (4WIDS) robot possesses high maneuverability, with exploiting its stemming 8-DoF (Degrees of Freedom) control inputs, for navigation itself in complex, obstacle-rich environments. In such scenarios, Model Predictive Path Integral (MPPI) control, a sampling-based approach to model predictive control, has emerged as a powerful technique. While MPPI can effectively handle nonlinear dynamics and non-differentiable cost functions, it confronts the fundamental challenge of curse of dimensionality, where the number of required samples grows exponentially with the dimension of the control space. Although dimensionality reduction of the control space is a known countermeasure for suppressing the computational burden of MPPI, a systematic analysis for rationally designing the reduced space remains as an open issue. This research therefore addresses this issue by first proposing a novel metric, Maneuverability Ellipsoid of the 4WIDS, to quantify the robot's maneuvering capability with regard to the multiple DoFs of the robot control inputs. Based on this ellipsoid, we numerically analyze a sampling method for selecting variables that contribute higher maneuverability in the MPPI framework. The robot maneuverability index is also proposed that is quantified by the size and shape of the manipulability ellipsoid. Through simulations, we demonstrate that this index significantly correlates with the success rate of robot navigation.

Collaborative exploration using unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has become increasingly popular in the past decade. This study addresses real-time autonomous tracking and landing of a UAV on a moving ground vehicle, which is fundamental for the UAV-UGV collaborative exploration. The method proposed in this study estimates the relative pose and velocity between a UAV and UGV, and uses model predictive control for UAV trajectory planning while considering the field of view of the camera onboard the UAV. We elaborate the hardware-in-the-loop simulator (HITL) with a physical companion computer, and confirm that the proposed method enables a UAV to land on a UGV traversing on rough terrain based on online computations in the HITL. Additionally, we present statistical analysis of the simulation results of typical and computationally demanding scenarios to elucidate the computational cost on the real machine.

Robotic mobility analysis in rough terrain is essential for mission success on robots deployed on planetary surfaces, construction, or disaster sites. A Hardware-in-the-loop Simulation (HILS) is known as an accurate and feasible method for dynamic analysis. The HILS is the hybrid approach that considers the contact dynamics of a robot in an actual environment and calculates the robot vehicle dynamics in a numerical simulation. We developed a HILS for wheeled mobile robot in loose terrain using a single wheel test bed. The HILS is verified under several traction load conditions. Further, the HILS is coupled with a wheel contact model based on the Dynamic Resistive Force Theory (DRFT). This HILS-DRFT can simultaneously simulate multiple wheels of the mobile robot. To improve the reliability of the DRFT, we implemented a real-time tuning process for the scaling factor used in the DRFT based on the wheel sinkage. The HILS-DRFT with the real-time tuning accurately reproduces the driving force of the actual vehicle.

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.

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.

There is a possibility of remaining indication of microorganisms on Martian subsurface and therefore, a robotic arm mounted on an exploration robot is required to dig to a certain depth and collect appropriate sample to be analyzed. However, the environment on the surface of Mars is harsh and most of all, limited power is available from the solar panel. In this paper, FEMI (Force-and-Energy Manipulability Index) is proposed to evaluate a feasible arm configuration for low energy consumption in its soil sampling operation. FEMI is calculated by the combination of an energy manipulability of an arm and an external force generated at an end effector of the arm. The FEMI derives the most feasible configuration on the joint angles of the arm for each sampling point. The usefulness of the FEMI is confirmed through a numerical simulation of a robotic arm. The simulation also presents that the FEMI can be used to obtain mechanical parameters of the arm such as link length and motor power, that are optimally-designed for a certain mission.

© Springer Nature Switzerland AG 2019. In disaster areas, operating heavy construction equipment remotely and autonomously is necessary, but conventional remote-controlled heavy equipment has problems such as insufficient operability, limited mobility on slopes and stairs, and low work efficiency because of difficult remote control. As part of the ImPACT-TRC Program, a group of Japanese researchers attempts to solve these problems by developing a construction robot for disaster relief tasks with a new mechanism and new control methods. This chapter presents the overview of construction robot and the details of main elemental technologies making up the robot. Section 5.1 describes the basic configuration of the robot and the teleoperation system. Section 5.2 is a tether powered drone which provides extra visual information. Sections 5.4 and 5.3 are force and tactile feedback for skillful teleoperation. Section 5.5 is visual information feedback which consists of an arbitrary viewpoint visualization system and a visible and LWIR camera system to observe surrounding of the robot in a dark night scene and/or a very foggy scene. These functions can dramatically increase construction equipment’s capacity to deal with large-scale disasters and accidents.

Traversing soft terrain poses a major challenge for planetary wheeled rovers, and various studies have demonstrated ways to enhance rover mobility by transforming the wheel structure or adjusting the wheel's stiffness, which results in a change in wheel contact area on the terrain. This paper presents a novel idea using the jamming mechanism for modulating the wheel's stiffness. The developed wheel consists of the core body, wheel outer rim, inner flexure, and cable tension mechanism. The jamming mechanism is realized by adjusting the cable tension inserted between the outer rim of the wheel. The wheel stiffness measuement test confirms that the wheel with low stiffness can reduce its stiffness for 75% of the high stiffness configuration. The wheel's traversability on soft terrain are also evaluated based on slip ratio and current consumption. The results demonstrate that the lower-stiffness configuration outperforms the higher-stiffness wheel under various conditions. These findings, being consistent with previous works on flexible wheels, highlight the potential benefits of the jamming-based stiffness-adjustable wheel for rough terrain traverse with various payload conditions.