Genya Ishigami

Design, Development, and Mobility Evaluation of an Omnidirectional Mobile Robot for Rough Terrain

Omnidirectional vehicles have been widely applied in several areas, but most of them are designed for the case of motion on flat, smooth terrain, and are not feasible for outdoor usage. This paper presents the design and development of an omnidirectional mobile robot that possesses high mobility in rough terrain. The omnidirectional robot consists of a main body with four sets of mobility modules, called an active split offset caster ASOC. The ASOC module has independently driven dual wheels that produce arbitrary planar translational velocity, enabling the robot to achieve its omnidirectional motion. Each module is connected to the main body via a parallel link with shock absorbers, allowing the robot to conform to uneven terrain. In this paper, the design and development of the ASOC-driven omnidirectional mobile robot for rough terrain are described. A control scheme that considers the kinematics of the omnidirectional mobile robot is presented. The mobility of the robot is also evaluated experimentally based on a metric called the ASOC mobility index. The mobility evaluation test clarifies a design tradeoff between terrain adaptability and omnidirectional mobility due to the shock absorbers. In addition, an odometry improvement technique that can reduce position estimation error due to wheel slippage is proposed. Experimental odometry tests confirmed that the proposed technique is able to improve the odometry accuracy for sharp-turning maneuvers.

Range-dependent Terrain Mapping and Multipath Planning using Cylindrical Coordinates for a Planetary Exploration Rover

This paper presents terrain mapping and path-planning techniques that are key issues for autonomous mobility of a planetary exploration rover. In this work, a LIDAR (light detection and ranging) sensor is used to obtain geometric information on the terrain. A point cloud of the terrain feature provided from the LIDAR sensor is usually converted to a digital elevation map. A sector-shaped reference grid for the conversion process is proposed in this paper, resulting in an elevation map with cylindrical coordinates termed as C2DEM. This conversion approach achieves a range-dependent resolution for the terrain mapping: a detailed terrain representation near the rover and a sparse representation far from the rover. The path planning utilizes a cost function composed of terrain inclination, terrain roughness, and path length indices, each of which is subject to a weighting factor. The multipath planning developed in this paper first explores possible sets of weighting factors and generates multiple candidate paths. The most feasible path is then determined by a comparative evaluation between the candidate paths. Field experiments with a rover prototype at a Lunar/Martian analog site were performed to confirm the feasibility of the proposed techniques, including the range-dependent terrain mapping with C2DEM and the multipath-planning method.

Terrain adaptive detector selection for visual odometry in natural scenes

Pose estimation is one of the important tasks for mobile robots exploring in outdoor environments. Recently, visual odometry has received a lot of attention since its localization is accurate even with low-cost sensors. Furthermore, the technique is not affected by wheel slips, and it can be performed without external infrastructures and preliminary maps. While existing techniques successfully provide good localization of outdoor vehicles, possible failures are not yet fully examined in untextured terrains where feature tracking occasionally fails. This paper proposes an approach to detect interest points from a wide variety of terrains by adaptively selecting algorithms. Experiments show that the approach provides robust and fast interest point detection even in untextured natural scenes. Graphical Abstract

Energy efficient slope traversability planning for mobile robot in loose soil

This paper proposes an energy-efficient trajectory planning method for a wheeled robot in slope ascending scenario. This method basically exploits a power consumption model of the robot which is obtained from the following two phases: first, the values of the robot power consumption in different slope angle, robot velocity, and robot heading angle are numerically calculated using a dynamic simulation of the robot taking into account of an accurate wheel-soil interaction mechanics; and subsequently, an approximated model for the robot power consumption is elaborated by neural network. Using the power consumption model an energy-efficient trajectory for a slope traversal case can be generated. Here, a bezier curve is used to provide a smooth trajectory designed with an appropriate arrival time as well as the control points for the curve. The numerical simulation result of the trajectory planning based on the proposed method gives several insights for a feasible trajectory for slope ascending scenario.

Modeling and Control of Robots on Rough Terrain

In this chapter, we introduce modeling and control for wheeled mobile robots and tracked vehicles. The target environment is rough terrains, which includes both deformable soil and heaps of rubble. Therefore, the topics are roughly divided into two categories, wheeled robots on deformable soil and tracked vehicles on heaps of rubble.

Gyro-based odometry associated with steering characteristics for wheeled mobile robot in rough terrain

Abstract 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. Graphical Abstract

Generalized Force-and-Energy Manipulability for design and control of redundant robotic arm

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.

Particle filter based 3D position tracking for terrain rovers using laser point clouds

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.

An Examination of Feature Detection for Real-Time Visual Odometry in Untextured Natural Terrain

Estimating the position of a robot is an essential requirement for autonomous mobile robots. Visual Odometry is a promising localization method in slippery natural terrain, which drastically degrades the accuracy of Wheel Odometry, while relying neither on other infrastructure nor any prior knowledge. Visual Odometry, however, suffers from the instability of feature extraction from the untextured natural terrain. To date, a number of feature detectors have been proposed for stable feature detection. This paper compares commonly used detectors in terms of robustness, localization accuracy and computational efficiency, and points out their trade-off problems among those criteria. To solve the problem, a hybrid algorithm is proposed which dynamically switches between multiple detectors according to the texture of terrain. Validity of the algorithm is proved by the simulation using dataset at volcanic areas in Japan.

Design, Development, and Mobility Test of an Omnidirectional Mobile Robot for Rough Terrain.

Omnidirectional vehicles have been developed and widely applied in several areas, but most of them are designed for the case of motion on flat, smooth terrain, and are not feasible for outdoor usage. This paper presents an omnidirectional mobile robot that possesses high mobility in rough terrain. The omnidirectional robot employs four sets of modules called active split offset caster (ASOC). The ASOC module has two independently-driven wheels that produce arbitrary planar translational velocity, enabling the robot to achieve its omnidirectional mobility. Each module is connected to the main body of the robot via a parallel link with shock absorbers, allowing the robot to conform to uneven terrain. In this paper, a design and development for the ASOC-driven omnidirectional mobile robot in rough terrain are described. Also, a control scheme that takes into account a kinematics of the omnidirectional mobile robot is presented. The omnidirectional mobility of the robot regardless of ifs heading direction is experimentally evaluated based on a metric called omnidirectional mobility index.