A study of free-form shape rationalization using biomimicry as inspiration

Bridging the gap between the material and geometrical aspects of a structure is critical in lightweight construction. Throughout the history of structural development, shape rationalization has been of prime focus for designers and architects, with biological forms being a major source of inspiration. In this work, an attempt is made to integrate different phases of design, construction, and fabrication under a single framework of parametric modeling with the help of visual programming. The idea is to offer a novel free-form shape rationalization process that can be realized with unidirectional materials. Taking inspiration from the growth of a plant, we established a relationship between form and force, which can be translated into different shapes using mathematical operators. Different prototypes of generated shapes were constructed using a combination of existing manufacturing processes to test the validity of the concept in both isotropic and anisotropic material domains. Moreover, for each material/manufacturing combination, generated geometrical shapes were compared with other equivalent and more conventional geometrical constructions, with compressive load-test results being the qualitative measure for each use case. Eventually, a 6-axis robot emulator was integrated with the setup, and corresponding adjustments were made such that a true free-form geometry could be visualized in a 3D space, thus closing the loop of digital fabrication

Bayesian estimation of human impedance and motion intention for human-robot collaboration

This article proposes a Bayesian method to acquire the estimation of human impedance and motion intention in a human-robot collaborative task. Combining with the prior knowledge of human stiffness, estimated stiffness obeying Gaussian distribution is obtained by Bayesian estimation, and human motion intention can be also estimated. An adaptive impedance control strategy is employed to track a target impedance model and neural networks are used to compensate for uncertainties in robotic dynamics. Comparative simulation results are carried out to verify the effectiveness of estimation method and emphasize the advantages of the proposed control strategy. The experiment, performed on Baxter robot platform, illustrates a good system performance

Basil Leaf Automation

Recent population and wage increases have forced farmers to grow more food without a proportionate increase in work force. Automation is a key factor in reducing cost and increasing efficiency. In this paper, we explore our automation solution that utilizes position manipulation and vision processing to identify, pick up, and drop a leaf into a can. Two stepper motors and a linear actuator drove the three-dimensional actuation. Leaf and can recognition were accomplished through edge detection and machine learning algorithms. Testing proved subsystem-level functionality and proof of concept of a delicate autonomous pick-and-place robot

A survey of the benefits and issues arising from the deployment of physical artefacts in computer science teaching

This paper describes the introduction of the use of physical artefacts in the teaching of the curriculum in the Department of Computer Science at Middlesex University. The rationale for the change is discussed, together with a description of the various technologies and the areas in which they were deployed. We conclude with a discussion of the outcomes of the work and the conclusions reached, prime amongst which are that the policy has been successful in motivating and engaging students, with a resultant improvement in student progression. In addition to their value in the taught part of the curriculum, these technologies have enabled students to become involved in real-world projects, interacting with external organizations and producing products of value in diverse areas such as the arts and assistive technologies

The Unified Behavior Framework for the Simulation of Autonomous Agents

Since the 1980s, researchers have designed a variety of robot control architectures intending to imbue robots with some degree of autonomy. A recently developed architecture, the UBF, implements a variation of the three-layer architecture with a reactive controller to rapidly make behavior decisions. Additionally, the UBF utilizes software design patterns that promote the reuse of code and free designers to dynamically switch between behavior paradigms. This paper explores the application of the UBF to the simulation domain. By employing software engineering principles to implement the UBF architecture within an open-source simulation framework, we have extended the versatility of both. The consolidation of these frameworks assists the designer in efficiently constructing simulations of one or more autonomous agents that exhibit similar behaviors. A typical air-to-air engagement scenario between six UBF agents controlling both friendly and enemy aircraft demonstrates the utility of the UBF architecture as a flexible mechanism for reusing behavior code and rapidly creating autonomous agents in simulation