Darboux-Frame-Based Parametrization for a Spin-Rolling Sphere on a Plane: A Nonlinear Transformation of Underactuated System to Fully-Actuated Model

This paper presents a new kinematic model based on the Darboux frame for motion control and planning. In this work, we show that an underactuated model of a spin-rolling sphere on a plane with five states and three inputs can be transformed into a fully-actuated one by a given Darboux frame transformation. This nonlinear state transformation establishes a geometric model that is different from conventional state-space ones. First, a kinematic model of the Darboux frame at the contact point of the rolling sphere is established. Next, we propose a virtual surface that is trapped between the sphere and the contact plane. This virtual surface is used for generating arc-length-based inputs for controlling the contact trajectories on the sphere and the plane. Finally, we discuss the controllability of this new model. In the future, we will design a geometric path planning method for the proposed kinematic model.Comment: 17 pages, 7 figures, Accepted at Mechanism and Machine Theory Elsevie

Effects of the slope on the motion of spherical RollRoller robot

In this paper, the effect of the slope on the locomotion of a spherical mobile robot named RollRoller is investigated under simulation. We analyze the robot motion up to 30 degrees of the slope inclination. The analysis is conducted for different conditions depending on the torque input and algorithmic motion planning. Oak fiber is chosen as the material of the inclined surface material, and the spherical shell of the robot is made of plastic. It is shown that RollRoller can move in different physical manners. As the velocity of the driving mass (the core) increases, certain series of jumping impulses take place because of predominant angular momentum. This pattern can support the motion of the sphere with accelerating climb in vertical axis. However, algorithmic-base position control of the RollRoller can prevent certain circular jumping impulses

A geometric motion planning for a spin-rolling sphere on a plane

The paper deals with motion planning for a spin-rolling sphere when the sphere follows an optimal straight path on a plane. Since the straight line constrains the sphere’s motion, controlling the sphere’s spin motion is essential to converge to a desired full configuration of the sphere. In this paper, we show a new geometric-based planning approach that is based on a full-state description of this nonlinear system. First, the problem statement of the motion planning is posed. Next, we develop a geometric controller implemented as a virtual surface by using the Darboux frame kinematics. This virtual surface generates arc-length-based inputs for controlling the trajectories of the sphere. Then, an iterative algorithm is designed to tune these inputs for the desired configurations. Finally, the feasibility of the proposed approach is verified by simulations

GLSkeleton: A geometric Laplacian-based skeletonisation framework for object point clouds

The curve skeleton is known to geometric modelling and computer graphics communities as one of the shape descriptors which intuitively indicates the topological properties of the objects. In recent years, studies have also suggested the potential of applying curve skeletons to assist robotic reasoning and planning. However, the raw scanned point cloud model is typically incomplete and noisy. Besides, dealing with a large point cloud is also computationally inefficient. Focusing on the curve skeletonisation of incomplete and poorly distributed point clouds of objects, an efficient geometric Laplacian-based skeletonisation framework (GLSkeleton) is proposed in this work. We also present the computational efficiency of the introduced local reduction strategy (LPR) approach without sacrificing the main topological structure. Comprehensive experiments have been conducted to benchmark performance using an open-source dataset, and they have demonstrated a significant improvement in both contraction and overall skeletonisation computational speed

Inverse dynamics-based motion control of a fluid-actuated rolling robot

In this paper, the rest-to-rest motion planning problem of a fluid-actuated spherical robot is studied. The robot is driven by moving a spherical mass within a circular fluid-filled pipe fixed internally to the spherical shell. A mathematical model of the robot is established and two inverse dynamics-based feed-forward control methods are proposed. They parameterize the motion of the outer shell or the internal moving mass as weighted Beta functions. The feasibility of the proposed feed-forward control schemes is verified under simulations

Cooperation of assistive robots to improve productivity in the nursing care field

This paper introduces an overview of the “Adaptable AI-enabled Robots to Create a Vibrant Society” project, which is part of the “Moonshot R &D Program” led by the Cabinet Office of Japan. We also introduce CARE, Cooperation of Ai-Robot Enablers, which are being researched and developed to improve productivity in the nursing care field. The importance of building an educational system for the successful use of advanced technologies will also be presented, and then we propose a nursing care motion guidance system using AR glasses that allows non-expert caregivers to learn appropriate nursing care

Geared rod-driven continuum robot with woodpecker-inspired extension mechanism and IMU-based force sensing

Continuum robot arms that can access confined spaces are useful in many applications, such as invasive surgery, search and rescue, and inspection. However, their reach is often limited because their extension mechanism relies on elastic deformation or folding structures. To address this challenge, we propose a continuum robot with a novel extension mechanism inspired by the impressive ability of woodpeckers to extend and bend their long tongues to catch insects in tree holes. The proposed mechanism can change the effective length of the robot from almost zero to any length by moving the robot's body back and forth. Our prototype robot demonstrated a maximum extension of 450 mm and a minimum bending radius of 125 mm. In addition, we developed a Gaussian process regression model to predict an external force applied to the robot's tip using inertial measurement units. This enabled us to determine the magnitude and direction of the force with an error rate of 4.8 percent and 11.1 percent, even when the robot's length was varied between the training and test data. The unrestricted extension capability of the proposed approach has the potential to increase the application prospects of continuum robots