This study proposes a computational method for approximating the Minkowski sum of two ellipsoids in three-dimensional space using a superellipsoid. Computing the Minkowski sum using high-precision mesh generation is expensive. Therefore, methods for approximating the Minkowski sum using functional representations have been proposed. In particular, numerous approaches use ellipsoids for approximation but suffer from accuracy limitations. The shape matrix and exponents of the superellipsoid are derived through a closed-form computation with constant time complexity of O ( 1 ) , independent of any boundary sampling resolution. Moreover, because the superellipsoid is an implicit function, the inside–outside testing of points is straightforward and requires only the evaluation of an inequality. In our experiments, we evaluate various parameter combinations for two general ellipsoids. The results demonstrate that the superellipsoid approximates the Minkowski sum with small error. Additionally, a comparison with an existing method that approximates the Minkowski sum of rotational ellipsoids using superellipsoids shows comparable accuracy, while the proposed method generalizes the approach to arbitrary ellipsoids. Regarding execution time, the method exhibits consistently fast and stable performance, as it relies solely on closed-form computation. The theoretical framework of this method has the potential to be extended to N -dimensional spaces, and is expected to find applications not only in rigid body simulations in three dimensions but also in computational tasks, such as grasp stability evaluation for robotics in six dimensions.

Abstract In this paper, we propose a fast and accurate method for approximating the Minkowski sum of two rotational ellipsoids with a superellipsoid. The Minkowski sum is used in a variety of applications such as robot motion planning and particle flow simulation requiring collision detection. Many of them are computed based on Minkowski sum, whose accuracy and processing time depend on how the mesh is created. We approximate Minkowski sum with a superellipsoid function. The superellipsoid has various shapes with the value of the exponents, and the computation of the parameters including the exponents is an algebraic computation with the time complexity $$\varvec{O}(1)$$ O ( 1 ) . As a result, approximation error is small and computation is fast in all combinations of rotational ellipsoids. In addition, collision is quickly detected by solving the inequality of superellipsoid.

This study presents a method for estimating the three-dimensional (3D) shapes of transparent objects from an RGB-D image using a statistical shape model. Statistical shape models compress the dimensions of multiple shapes to represent shape variations using fewer parameters. It is difficult to measure the depth of a transparent object using sensors. Therefore, the statistical shape model is deformed to fit the contour extracted from an RGB image and estimate the shape of the object. The depth image is used only to detect the plane on which the transparent objects are placed. Unlike other estimation methods, the proposed method estimates the whole shape of a transparent object. To validate the proposed method, the obtained estimation accuracy is compared with that of a machine-learning-based method. In addition, the estimated whole shape is compared with the measured data from a 3D scanner.

Casting manipulation has been studied to expand the robot’s movable range. In this manipulation, the robot throws and reaches the end effector to a distant target. Usually, a special casting manipulator, which consists of rigid arm links and specific flexible linear objects, is constructed for an effective casting manipulation. However, the special manipulator cannot perform normal manipulations, such as picking and placing, grasping, and operating objects. We propose that the normal robot arm, which can perform normal tasks, picks up an unknown string in the surrounding environment and realizes casting manipulation with it. As the properties of the string are not provided in advance, it is crucial how to reflect it in casting manipulation. This is realized by the motion generation of the robot arm with the simulation of string movement, actual string manipulation by the robot arm, and string parameter estimation from the actual string movement. After repeating these three steps, the simulated string movement approximates the actual to realize casting manipulation with the unknown string. We confirmed the effectiveness of the proposed method through experiments. The try of this study will lead to enhancement of the performance of home service robot, exploration robot, rescue robot and entertainment robot.

Quickness, preciseness and robustness are required in manipulation tasks of robotic hands for automation of manufacturing sites. Previous researches have found that sensing from fingertips equipped with proximity sensors is available for the requirements, because it complements blind areas of vision sensors. In this paper, we develop a novel optical proximity sensor for robot fingertips which provides two levels of proximity information with different purposes, sampling rates, information quantity and quality. The lower-level information from the sensor is for high-speed feedback control of a robotic hand, and the higher-level information is for recognizing the shape and size of an object. A prototype of the sensor with 5 × 5 matrix of photo detectors is presented, and its availability is shown through basic characteristic tests. A motion experiment using a robotic hand equipped with the prototype sensors is also conducted. The result confirms that the robotic hand can adjust the position and orientation of the fingertips to various objects and then correct the grasping form according to the object size within 1s.

This paper proposes new software and hardware platforms named ROS-TMS and Big Sensor Box, respectively, for an informationally structured environment. We started the development of a management system for an informationally structured environment named Town Management System (TMS) in the Robot Town Project in 2005. Since then we have been continuing our efforts to improve performance and to enhance TMS functions. Recently, we launched a new version of TMS named ROS-TMS, which resolves some critical problems in TMS by adopting the Robot Operating System (ROS) and utilizing the high scalability and numerous resources of ROS. In this paper, we first discuss the structure of a software platform for the informationally structured environment and describe in detail our latest system, ROS-TMS version 4.0. Next, we introduce a hardware platform for the informationally structured environment named Big Sensor Box, in which a variety of sensors are embedded and service robots are operated according to the structured information under the management of ROS-TMS. Robot service experiments including a fetch-and-give task and autonomous control of a wheelchair robot are also conducted in Big Sensor Box.

This paper presents methodologies for dexterous manipulation by an underactuated robotic soft gripper with a low DOF. While the softness and passive joints provide a stable grasp, the manipulations become challenging owing to the complexities of modeling and state estimation. To investigate the drawbacks, target manipulations using a support surface and gravity are defined in this study. By realizing the target manipulations, methodologies for utilizing both the support surface and gravity in manipulation are validated. For manipulation utilizing the support surface, the key states - at which the type of gripper motion primitive changes - are defined, and gripper motion at the key states is produced with a DNN-based motion generator. For manipulation utilizing gravity, the fall risk of the object is formulated as a constraint for a criterion function, and a parameters-online-exploration based methodology is adopted. The validity of the methodologies is demonstrated through several experiments.

This paper proposes a new method for mapping volume models of human organs onto a target volume with simple shapes. The proposed method is based on our modified Self-organizing Deformable Model (mSDM) which finds the one-to-one mapping with no foldovers between an arbitrary object surface model and a target surface. By extending mSDM to apply to organ volume models, the proposed method, called volumetric SDM (vSDM), establishes the one-to-one correspondence between the volume model and its target volume. At the same time, vSDM preserves geometrical properties of the original model before and after the mapping. In addition, vSDM allows to control the mapping of interior structures of the organ model onto specific regions inside the target volume. These characteristics of vSDM enables to easily find a reliable correspondence between different volume models via a common target volume.

We propose an object tracking system which recognizes everyday objects and estimates their positions by using distributed sensors in a room and mobile robots. The placement of objects is frequently changed according to human activities. Although a passive RFID tag is attached to each object for the object's recognition, the placement is often not uniquely determined due to the deficiency of measured data. We have already proposed a method for estimating the placement of objects by using the moving trajectories of objects. This estimation result is expressed as the probability distribution of the object placement. However intersections of trajectories cause the decrease of the estimation accuracy. So we propose a new method based on Bayesian inference to improve the estimation accuracy by using the size and the shape of an object measured by laser range finder. Then a mobile robot settles the placement with small workload by using the mounted sensor. The system successfully recognized and localized 10 objects in the experiment.

In this study, we experimentally investigated the effect of robot fingertip stiffness on the maximum resistible force. The maximum resistible force is defined as the maximum tangential force at which the fingertip can maintain contact when applying and increasing tangential/shearing force. We include in the definition of this term the effect of fingertip deformation. In contrast to our previous study [11], cylindrical fingertips with flat surfaces were used in this study so that the contact area would remain the same when there was no tangential/shearing force. This made it possible to see the effect of fingertip stiffness more clearly. We also investigated the effect of curvature of the contact surface, which was not investigated in depth in [11]. The main findings are as follows. 1) Harder fingertips produce larger resistible forces, irrespective of the shape of the contact surface (flat or curved). 2) For harder fingertips, the maximum resistible force depends largely on the shape of the contact surface, while for softer fingertips, the shape has little effect. 3) For softer fingertips, the magnitude of the resistible force changes little even when the normal force increases.

We propose an evaluation method of grasp stability which takes into account the elastic deformation of fingertips from the viewpoint of energy. An evaluation value of grasp stability is derived as the minimum energy which causes slippage of a fingertip on its contact surface. To formulate the evaluation value, the elastic potential energy of fingertips and the gravitational potential energy of a grasped object are considered. It is ensured that fingertips do not slip on grasped object surfaces if the external energy applied to the object is less than the evaluation value. Since our evaluation value explicitly considers the deformation values of fingertips, grasp stability is evaluated by taking into consideration the contact forces generated by the deformation. The effectiveness of our method is verified through numerical examples.

In this paper, we propose a general manipulation planner for dual-arm industrial manipulators. According to the context, the planner automatically determines whether both arms have to be used simultaneously or not. The approach is based on (i) the extension of an object placement algorithm previously developed in [23], and (ii) the introduction of several types of re-grasping motions dedicated to dual-arm manipulators. Such motions induce a special topological structure in the manipulation space that can be captured into a manipulation graph. The graph is then used to solve the manipulation problem by a simple graph search algorithm. After searching for a solution path, we further consider optimizing the path by minimizing the number of re-grasps. The effectiveness of the approach is demonstrated on the dual-arm manipulator HiroNX working in a realistic factory environment.

We discuss grasp stability under gravity where each finger makes soft-finger contact with an object. By clustering polygon models of a finger and an object, the contact area between a finger and an object is obtained as the common area between an object cluster and a finger cluster. Then, by assuming the Winkler elastic foundation, the pressure distribution within the contact area is obtained. By using this pressure distribution, we show that we can judge grasp stability under soft-finger contact. We further consider defining a quality measure of a soft-finger grasp by assuming that although the gravitational force is applied to an object, the direction of gravity is unknown. To demonstrate the effectiveness of the proposed approach, we show several numerical examples.

This paper presents a grasp planner which allows a robot to grasp the constricted parts of objects in our daily life. Even though constricted parts can be grasped more firmly than convex parts, previous planners have not sufficiently focused on grasping this part. We develop techniques for quadric surface approximation, grasp posture generation, and stability evaluation for grasping constricted parts. By modeling an object into multiple quadric surfaces, the planner generates a grasping posture by selecting one-sheet hyperbolic surfaces or two adjacent ellipsoids as constricted parts. When a grasping posture being generated, the grasp stability is evaluated based on the distribution of the stress applied to an object by the fingers. We perform several simulations and experiments to verify the effectiveness of our proposed method.

This paper proposes a method for bin-picking for objects without assuming the precise geometrical model of objects. We consider the case where the shape of objects are not uniform but are similarly approximated by cylinders. By using the point cloud of a single object, we extract the probabilistic properties with respect to the difference between an object and a cylinder and consider applying the probabilistic properties to the pick-and-place motion planner of an object stacked on a table. By using the probabilistic properties, we can also realize the contact state where a finger maintain contact with the target object while avoiding contact with other objects. We further consider approximating the region occupied by fingers by a rectangular parallelepiped. The pick-and-place motion is planned by using a set of regions in combination with the probabilistic properties. Finally, the effectiveness of the proposed method is confirmed by some numerical examples and experimental result.

Dexterous manipulation is an important function for working robots. Manipulator tasks such as grasping, assembly and disassembly can generally be divided into several motion primitives. We call such motion primitives “skills” and explain how most manipulator tasks can be composed of sequences of these skills. We will address the issues involved with various types of robots such as maintenance robots and service robots. We have considered hierarchizing the manipulation tasks of these robots since their tasks have become more complex than ever before. Additionally, as errors are seen likely to increase in complex tasks, it is important to implement effective error recovery technology. This paper presents our proposal for a new type of error recovery that uses the concepts of task stratification and error classification which can be expressed specifically using flow charts.

This paper proposes a method for planning the pick-and-place motion of an object by dual-arm manipulators. Our planner is composed of the offline and the online phases. The offline phase generates a set of regions on the object and the environment surfaces and calculates several parameters needed in the online phase. In the online phase, the planner selects a grasping pose of the robot and a putting posture of the object by searching for the regions calculated in the offline phase. By using the proposed method, we can also plan the trajectory of the robot, and the regrasping strategy of the dual-arm. Here, the putting posture of the object can be planned by considering stability of the object placed on the environment. The effectiveness of the proposed method is confirmed by simulation and experimental results by using the dual-arm robot NX-HIRO.

This paper proposes an object placement planner for a grasped object during pick-and-place tasks. The proposed planner automatically determines the pose of an object stably placed near a user assigned point on an environment surface. The proposed method first constructs a polygon model of the surrounding environment, and then clusters the polygon model of both the environment and the object where each cluster is approximated by a planar region. The placement of the object can be determined by selecting a pair of clusters between the object and the environment. We further impose several conditions to determine the pose of the object placed on the environment. We show that we can determine the position/orientation of the object placed on the environment for several cases such as hanging a mug cup on a bar. The effectiveness of the proposed research is confirmed through several numerical examples.

Hardware improvement of cybernetic human HRP-4C for entertainment is presented in this paper. We coined the word ¿Cybernetic Human¿ to explain a humanoid robot with a realistic head and a realistic figure of a human being. HRP-4C stands for Humanoid Robotics Platform-4 (Cybernetic human). Its joints and dimensions conform to average values of young Japanese females and HRP-4C looks very human-like. We have made HRP-4C present in several events to search for a possibility of use in the entertainment industry. Based on feedback from our experience, we improved its hardware. The new hand, the new foot with active toe joint, and the new eye with camera are introduced.

In this paper, we generate the biped gait of a humanoid robot that looks like a human's one. To generate the human like motion, we first capture walking motion of a human. Then, we analyze the captured data and obtain several information such as the relationship between the step length and waist height etc. We consider applying these informations to the real humanoid robot. Also, when the human walks, the sway of the waist is smaller than most of the humanoid robot's one. By compensating the angular momentum of the robot and by modifying the ZMP trajectory, we show that sway of the robot's waist can be smaller. We show the effectiveness of the proposed method through simulation and experimental results.

This paper presents an easy and fast method of testing force closure when a multi-fingered hand grasps an object. Different from previous methods, we consider approximating the friction cone by using a few ellipsoids. By using this method, the total force/moment set applied to the grasped object can be obtained by a common set of multiple ellipsoids. This method is effective since we can test the force closure by simply calculating the inequalities of quadratic form. Moreover, by using the ellipsoidal approximation, we propose an easy method of evaluating the grasp stability. We show that the grasp stability can be calculated by using simple equations. The effectiveness of the proposed method is verified by several numerical examples where we show that the proposed method is fairly accurate and can evaluate the grasp stability faster than conventional methods.

In various application fields, high-speed cameras are used to analyze high-speed phenomena. Coded structured light projection methods have been proposed for acquiring three-dimensional images. Most of them are not suitable for measuring high-speed phenomena because the errors are caused when the measured objects move due to light projection of multiple patterns. In this paper, we propose a new coded structured light projection method that can select not only a temporal encoding but also a spatial encoding adaptively for obtaining three-dimensional images at a high-speed frame rate. We also develop an evaluation system that uses a DLP projector and an off-line high-speed video camera, and verify the effectiveness of the proposed method by showing the obtained three-dimensional shapes for moving objects.

In this paper, we propose a finger-tapping interface called FINGERTAP, which can estimate the contact states and forces on human fingertips in real time by using only the fingertip positions measured by high-speed vision cameras. In particular, we focus on the high-frequency component that develops at the moment a fingertip contacts something. We introduce a real-time estimation algorithm for the fingertip contact state and force by using frequency filtering to detect the high-frequency movement component of the fingertip positions. We also introduce a clickable pointing interface and a virtual musical instrument as a demonstration of an application using the FINGERTAP system.

This work presents a new method of combining dynamic control of LOD and conservative occlusion culling based on a new hierarchical data structure of polygons. Our method is effective for rendering a large amount of data in complex environments.