Modelling of soldier fly halteres for gyroscopic oscillations

Nature has evolved a beautiful design for small-scale vibratory rategyro in the form of dipteran halteres that detect body rotations via Coriolis acceleration. In most Diptera, including soldier fly, Hermetia illucens, halteres are a pair of special organs, located in the space between the thorax and the abdomen. The halteres along with their connecting joint with the fly's body constitute a mechanism that is used for muscle-actuated oscillations of the halteres along the actuation direction. These oscillations lead to bending vibrations in the sensing direction (out of the haltere's actuation plane) upon any impressed rotation due to the resulting Coriolis force. This induced vibration is sensed by the sensory organs at the base of the haltere in order to determine the rate of rotation. In this study, we evaluate the boundary conditions and the stiffness of the anesthetized halteres along the actuation and the sensing direction. We take several cross-sectional SEM (scanning electron microscope) images of the soldier fly haltere and construct its three dimensional model to get the mass properties. Based on these measurements, we estimate the natural frequency along both actuation and sensing directions, propose a finite element model of the haltere's joint mechanism, and discuss the significance of the haltere's asymmetric cross-section. The estimated natural frequency along the actuation direction is within the range of the haltere's flapping frequency. However, the natural frequency along the sensing direction is roughly double the haltere's flapping frequency that provides a large bandwidth for sensing the rate of rotation to the soldier flies

Modeling strain sensing by the gyroscopic halteres, in the dipteran soldier fly, hermetia illucens

Dipteran insects are known to receive mechanosensory feedback on their aerial rotations from a pair of vibratory gyroscopic organs called halteres. Halteres are simple cantilever-like structures with an end mass that evolved from the hind wings of the ancestral four-winged insects form. In most Diptera, including the soldier fly Hermetia illucens, the halteres vibrate at the same frequency as the wings. These vibrations occur in a vertical plane such that any rotation about this plane imposes orthogonal Coriolis forces on the halteres causing their plane of vibration to shift laterally by a small degree. This motion results in strain variation at the base of the haltere shaft, which is sensed by the campaniform sensilla. This strain variation is, therefore, a key parameter for sensing body rotations. In this paper, we present a study of the basic mechanism of soldier fly halteres to demonstrate its use as a vibratory gyroscope. First, we use a static force sensor to determine the stiffness of the haltere, to evaluate the natural frequency along the flapping direction, followed by nanoindentation-based measurement of its elastic modulus. We then model the haltere as a simple structure with the measured material properties and carry out an analysis to estimate the gyroscopic strain. We also use Finite Element simulations to verify our estimates. This study is intended to provide a better understanding of the mechanism of the natural vibratory gyroscope

Optimization Complete Area Coverage by Reconfigurable hTrihex Tiling Robot

Completed area coverage planning (CACP) plays an essential role in various fields of robotics, such as area exploration, search, rescue, security, cleaning, and maintenance. Tiling robots with the ability to change their shape is a feasible solution to enhance the ability to cover predefined map areas with flexible sizes and to access the narrow space constraints. By dividing the map into sub-areas with the same size as the changeable robot shapes, the robot can plan the optimal movement to predetermined locations, transform its morphologies to cover the specific area, and ensure that the map is completely covered. The optimal navigation planning problem, including the least changing shape, shortest travel distance, and the lowest travel time while ensuring complete coverage of the map area, are solved in this paper. To this end, we propose the CACP framework for a tiling robot called hTrihex with three honeycomb shape modules. The robot can shift its shape into three different morphologies ensuring coverage of the map with a predetermined size. However, the ability to change shape also raises the complexity issues of the moving mechanisms. Therefore, the process of optimizing trajectories of the complete coverage is modeled according to the Traveling Salesman Problem (TSP) problem and solved by evolutionary approaches Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Hence, the costweight to clear a pair of waypoints in the TSP is defined as the required energy shift the robot between the two locations. This energy corresponds to the three operating processes of the hTrihex robot: transformation, translation, and orientation correction. The CACP framework is verified both in the simulation environment and in the real environment. From the experimental results, proposed CACP capable of generating the Pareto-optimal outcome that navigates the robot from the goal to destination in various workspaces, and the algorithm could be adopted to other tiling robot platforms with multiple configurations

Human-robot collaboration for unknown flexible surface exploration and treatment based on mesh iterative learning control

Contact tooling operations like sanding and polishing have been high in demand for robotics and automation, as manual operations are labour-intensive with inconsistent quality. However, automating these operations remains a challenge since they are highly dependent on prior knowledge about the geometry of the workpiece. While several methods have been developed in existing research to automate the geometry learning process and adjust the contact force, human supervision is heavily required in the calibration of work pieces and the path planning of robot motion in such methods. Furthermore, the stiffness identification of the work piece is not considered in most of these methods. This paper presents a human-robot collaboration (HRC) framework, which is able to perform surface exploration on an unknown object combining the operator’s flexibility with the control precision of the robot. The operator moves the robot along the surface of the target object, and the robot recognizes the surface geometry and surface stiffness while exerting a desired contact force through control. For this purpose, a mesh iterative learning control (MILC) is developed to learn the surface stiffness, plan the exploration path, and adjust contact force through repetitive online correction based on HRC. The proof of learning convergence and the results of the simulation and experiments performed using a 7-DOF Sawyer robot demonstrate the validity of the proposed controller.</p