論文

In this paper, the authors present a novel criterion for path planning based on the visibility index caused by obstacles detected through laser range sensors when exploring lunar craters. The proposed path planning algorithm calculates an index based on terrain roughness, path length and occlusion, and determines the areas where obstacles may limit the visibility of the area where the rover must go next. The derivation of the visibility index is explained in detail and the algorithm steps are described throughly. Simulations were carried out in order to test the proposed algorithm and a results are presented. © 2008 IEEE.

本論文では，月惑星探査ロボットの自律移動システムについて，特に下記の2点に注目したアプローチを構築した．（１）レーザ距離計の特性を反映した円柱座標系を用いた地図構築，（２）複数の経路生成手法による不整地走行に最適な経路の選択．テストベッドロボットを用いた屋外試験によって，これら提案手法の妥当性の評価を行った．

In this paper, a path planning and its evaluation method is described with taking into account wheel slip dynamics of lunar/planetary exploration rovers. The surface of the planetary body is largely covered with powdery soil. On such loose soil, the wheel slippage which will make the rover get stuck must be concerned. Since the slippage dynamically depends on the posture/velocity of vehicle, soil characteristics, and wheel-soil interactions, it becomes difficult issues to incorporate the wheel slip dynamics as a criterion into path-planning algorithms. To tackle the slippage problem, the authors develop the path-planning algorithm and the path-evaluation method based on the following approach. First, a path on a rough terrain is generated with the terrain-based criteria function. Subsequently, the dynamics simulation of a rover is carried out in which the rover is controlled to follow the candidate path. Finally, the path is properly evaluated based on the slip motion profiles calculated by the simulation. Demonstrations for the proposed technique are addressed along with a discussion on characteristics of the candidate path and the slip motion profile of the rover. © 2007 IEEE.

In this paper an omnidirectional mobile robot that possesses high mobility in rough terrain is presented. The omnidirectional robot has four active split offset caster (ASOC) modules, enabling the robot to move in any planar direction. It also possesses passive suspension articulation, allowing the robot to conform to uneven terrain. The agility of the robot is experimentally evaluated in various configurations. In addition, an odometry method that mitigates position estimation error due to wheel slippage is proposed. A key aspect of the proposed method is to utilize sensory data of wheel velocity, and turning rate around each ASOC pivot shaft, along with kinematic constraints of the robot configuration. Experimental odometry tests with different maneuvers in rough terrain are presented that confirm the utility of the proposed method. © 2011 IEEE.

移動ロボットの挙動解析における不確定性パラメータを明確に取り扱い，統計学的なアプローチと動力学モデルを融合することによって，効率的な計算手法を提案した．

異方性摩擦を有する車輪を設計，開発し，この車輪を複数個組み合わせることによって，従来よりも走破性能の高い全方向移動ロボットを提案した．

砂地上を移動する車輪ロボットの走行後の車輪の轍から，ロボットの位置・姿勢・滑りの推定を行う手法を提案し，同手法と車輪モデルとの融合による推定精度の向上について示した．

Difficult conditions on outdoor terrains make outdoor autonomy for rovers, a challenging task. The conventional wheel odometry method uses orientation measurements to assume a momentary plane to apply wheel encoder readings. On uneven terrains, this method often gives poor results for position tracking, and therefore rarely used. To improve the conventional odometry motion model, immediate terrain data can be used. This paper proposes a novel state variable extension (SVE) method to establish a connection between state space variables of a terrain rover by combining terrain point clouds with rover kinematics. The simulation results show that when the 2D state variables (x, y, yaw) are known, the 2D state can be extended to its 3D state (x, y, z, roll, pitch, yaw) with minimal error. The proposed SVE method is employed in a particle filter to determine the 2D state variables, which in turn results in achieving the full 3D position tracking of the rover.

In this paper, a path following control strategy for lunar/planetary exploration rovers is described, taking into account slip motion of the rover. It is determined that the slip motion of each wheel of the rover must be increased and cannot be neglected when the rover travels on loose soil. Because of slip, following an arbitrary path on loose soil is a difficult task. In order to improve this situation, the authors have developed a path following algorithm with slip compensation. In this algorithm, both steering and driving maneuvers of the rover are derived not only to follow an arbitrary path, but also simultaneously compensate for the slip. The performance of the path following strategy is confirmed through numerical simulation using the wheel-and-vehicle model elaborated in our previous research. The slip motion of the wheel is also addressed, based on a terramechanics approach. The proposed path following algorithm shows better performance than traditional control without slip compensation in the simulation. © 2006 IEEE.

This chapter presents a path planning and navigation framework for a planetary exploration rover and its experimental tests at a Lunar/Martian analog site. The framework developed in this work employs a laser range finder (LRF) for terrain feature mapping. The path planning algorithm generates a feasible path based on a cost function consisting of terrain inclination, terrain roughness, and path length. A set of navigation commands for the rover is then computed from the generated path. The rover executes those navigation commands to reach a desired goal. In this paper, a terrain mapping technique that uses a LRF is described along with an introduction to a cylindrical coordinate digital elevation map (C2DEM). The gird-based path planning algorithm is also presented. Field experiments regarding the path planning and navigation that evaluate the feasibility of the framework developed in this work are reported. © Springer-Verlag Berlin Heidelberg 2014.

2 : 共著

Planetary exploration rovers are required to (semi-) autonomously navigate itself on rough terrain. In such scenario, a feasible path to be followed must be accurately planned, allowing the rover to safely traverse without any mobility hazards. In this paper, a path planning and evaluation strategy that explicitly considers dynamic mobility of the rover is presented. The proposed strategy consists of the following three steps. First, various paths on a given terrain map are generated with varying weighting factors for path planning algorithm. Each path is then examined through complete dynamic simulations of the rover in which the rover travels along with the path. The simulation result provides a metric for robotic mobility. The metric, termed a dynamic mobility index, consists of stability of the rover, wheel slippage, elapsed time, and energy consumption. All of the paths generated are quantitatively evaluated based on the dynamic mobility index, and then, the most feasible path between them is obtained. Demonstrations for the path planning and evaluation are presented in this paper that confirms the validity of the proposed strategy. © 2011 IEEE.

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.