Decomposing CAD models of objects of daily use and reasoning about their functional parts

Abstract — Today’s robots are still lacking comprehensive knowledge bases about objects and their properties. Yet, a lot of knowledge is required when performing manipulation tasks to identify abstract concepts like a “handle ” or the “blade of a spatula ” and to ground them into concrete coordinate frames that can be used to parametrize the robot’s actions. In this paper, we present a system that enables robots to use CAD models of objects as a knowledge source and to perform logical inference about object components that have automatically been identified in these models. The system includes several algorithms for mesh segmentation and geometric primitive fitting which are integrated into the robot’s knowledge base as procedural attachments to the semantic representation. Bottom-up segmentation methods are complemented by top-down, knowledge-based analysis of the identified components. The evaluation on a diverse set of object models, downloaded from the Internet, shows that the algorithms are able to reliably detect several kinds of object parts. I

Artificial consciousness and the consciousness-attention dissociation

Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. This becomes clear when considering emotions and examining the dissociation between consciousness and attention in humans. While we may be able to program ethical behavior based on rules and machine learning, we will never be able to reproduce emotions or empathy by programming such control systems—these will be merely simulations. Arguments in favor of this claim include considerations about evolution, the neuropsychological aspects of emotions, and the dissociation between attention and consciousness found in humans. Ultimately, we are far from achieving artificial consciousness

Does Form follow Function? Connecting Function Modelling and Geometry Modelling for Design Space Exploration

The aerospace industry, representative of industries developing complex products, faces challenges from changes in user behaviour, legislation, environmental policy. Meeting these challenges will require the development of radically new products. Radically new technologies and solutions need to be explored, investigated, and integrated into existing aerospace component architectures. The currently available design space exploration (DSE) methods, mainly based around computer-aided design (CAD) modelling, do not provide sufficient support for this exploration. These methods often lack a representation of the product’s architecture in relation to its design rationale (DR)—they do not illustrate how form follows function. Hence, relations between different functions and solutions, as well as how novel ideas relate to the legacy design, are not captured. In particular, the connection between a product’s function and the embodiment of its solution is not captured in the applied product modelling approaches, and can therefore not be used in the product development process.To alleviate this situation, this thesis presents a combined function and geometry-modelling approach with automated generation of CAD models for variant concepts. The approach builds on enhanced function means (EF-M) modelling for representation of the design space and the legacy design’s position in it. EF-M is also used to capture novel design solutions and reference them to the legacy design’s architecture. A design automation (DA) approach based on modularisation of the CAD model, which in turn is based on the functional decomposition of the product concepts, is used to capture geometric product information. A combined function-geometry object model captures the relations between functions, solutions, and geometry. This allows for CAD models of concepts based on alternative solutions to be generated.The function- and geometry-exploration (FGE) approach has been developed and tested in collaboration with an aerospace manufacturing company. A proof-of-concept tool implementing the approach has been realised. The approach has been validated for decomposition, innovation, and embodiment of new concepts in multiple studies involving three different aerospace suppliers. Application of FGE provides knowledge capture and representation, connecting the teleological and geometric aspects of the product. Furthermore, it supports the exploration of increasingly novel solutions, enabling the coverage of a wider area of the design space.The connection between the modelling domains addresses a research gap for the “integration of function architectures with CAD models”.While the FGE approach has been tested in laboratory environments as well as in applied product development projects, further development is needed to refine CAD integration and user experience and integrate additional modelling domains

Task-adaptable, Pervasive Perception for Robots Performing Everyday Manipulation

Intelligent robotic agents that help us in our day-to-day chores have been an aspiration of robotics researchers for decades. More than fifty years since the creation of the first intelligent mobile robotic agent, robots are still struggling to perform seemingly simple tasks, such as setting or cleaning a table. One of the reasons for this is that the unstructured environments these robots are expected to work in impose demanding requirements on a robota s perception system. Depending on the manipulation task the robot is required to execute, different parts of the environment need to be examined, the objects in it found and functional parts of these identified. This is a challenging task, since the visual appearance of the objects and the variety of scenes they are found in are large. This thesis proposes to treat robotic visual perception for everyday manipulation tasks as an open question-asnswering problem. To this end RoboSherlock, a framework for creating task-adaptable, pervasive perception systems is presented. Using the framework, robot perception is addressed from a systema s perspective and contributions to the state-of-the-art are proposed that introduce several enhancements which scale robot perception toward the needs of human-level manipulation. The contributions of the thesis center around task-adaptability and pervasiveness of perception systems. A perception task-language and a language interpreter that generates task-relevant perception plans is proposed. The task-language and task-interpreter leverage the power of knowledge representation and knowledge-based reasoning in order to enhance the question-answering capabilities of the system. Pervasiveness, a seamless integration of past, present and future percepts, is achieved through three main contributions: a novel way for recording, replaying and inspecting perceptual episodic memories, a new perception component that enables pervasive operation and maintains an object belief state and a novel prospection component that enables robots to relive their past experiences and anticipate possible future scenarios. The contributions are validated through several real world robotic experiments that demonstrate how the proposed system enhances robot perception

Uses and applications of artificial intelligence in manufacturing

The purpose of the THESIS is to provide engineers and personnels with a overview of the concepts that underline Artificial Intelligence and Expert Systems. Artificial Intelligence is concerned with the developments of theories and techniques required to provide a computational engine with the abilities to perceive, think and act, in an intelligent manner in a complex environment. Expert system is branch of Artificial Intelligence where the methods of reasoning emulate those of human experts. Artificial Intelligence derives it\u27s power from its ability to represent complex forms of knowledge, some of it common sense, heuristic and symbolic, and the ability to apply the knowledge in searching for solutions. The Thesis will review : The components of an intelligent system, The basics of knowledge representation, Search based problem solving methods, Expert system technologies, Uses and applications of AI in various manufacturing areas like Design, Process Planning, Production Management, Energy Management, Quality Assurance, Manufacturing Simulation, Robotics, Machine Vision etc. Prime objectives of the Thesis are to understand the basic concepts underlying Artificial Intelligence and be able to identify where the technology may be applied in the field of Manufacturing Engineering

A Study of Case Based Reasoning Applied to Welding Computer Aided Fixture Design

This thesis focuses on the application of case based reasoning (CBR) to welding fixtures in a computer aided design (CAD) environment. Modular fixtures have become more popular in previous years due to the creation of flexible manufacturing systems. Modular fixtures, since they are composed of many standardized parts, require much iteration to produce a full fixture design. This process is made more complicated when it is applied to more complex parts such as welding assemblies. In an effort to simplify fixture design for such complicated parts, researchers have been working on integrating fixture design into CAD packages. These efforts, generally known as computer aided fixture design (CAFD), do not focus on the transition of experience from more experienced designers but only provide a structure and a virtual environment to create fixtures. The research presented in this thesis will apply to this area. Case based reasoning (CBR) is a method of using previous cases to help aid the development of solutions to new problems. Applied to CAFD, this method is reduced to the application of a database and a retrieval and adaptation system. Current research on CAFD and CBR is limited to only proposing systems for machining fixtures. This thesis presents a methodology of a CAFD and CBR system that is dedicated to welding assemblies and fixtures. The focus is on creating an indexing system that adequately represents the workpiece and fixture, a retrieval system that accurately recovers the previous cases, and a method that integrates designer feedback in each process. The results of this thesis will be shown in a case study using an automobile muffler fixture assembly to define each idea of the methodology and to provide an example