Requirement

In product development and process optimization, a requirement is a singular documented physical or functional need that a particular design, product or process aims to satisfy. It is commonly used in a formal sense in engineering design, including for example in systems engineering, software engineering, or enterprise engineering. It is a broad concept that could speak to any necessary (or sometimes desired) function, attribute, capability, characteristic, or quality of a system for it to have value and utility to a customer, organization, internal user, or other stakeholder. Requirements can come with different levels of specificity; for example, a requirement specification or requirement "spec" (often imprecisely referred to as "the" spec/specs, but there are actually different sorts of specifications) refers to an explicit, highly objective/clear (and often quantitative) requirement (or sometimes, set of requirements) to be satisfied by a material, design, product, or service.

Rigid body dynamics simulation for robot motion planning

Alan Ettlin

The development of robot motion planning algorithms is inherently a challenging task. This is more than ever true when the latest trends in motion planning are considered. Some motion planners can deal with kinematic and dynamic constraints induced by the mechanical structure of the robot. Another class of motion planners fulfill various types of optimality conditions, yet others include means of dealing with uncertainty about the robot and its environment. Sensor-based motion planners gather information typically afflicted with errors about a partially known environment in order to plan a trajectory therein. In another research area it is investigated how multiple robots best cooperate to solve a common task. In order to deal with the complexity of developing motion planning algorithms, it is proposed in this document to resort to a simulation environment. The advantages of doing so are outlined and a system named Ibex presented which is well suited to support motion planner development. The developed framework makes use of rigid body dynamics algorithms as simulation kernel. Further, various components are included which integrate the simulation into existing engineering environments. Simulation content can be conveniently developed through extensions of well-established 3D modelling tools. The co-simulation with components from other domains of physics is provided by the integration into a leading dynamic modelling environment. Robotic actuator models can be combined with a rigid body dynamics simulation using this mechanism. The same configuration also allows to conveniently develop control algorithms for a rigid body dynamics setup and offers powerful tools for handling and analysing simulation data. The developed simulation framework also offers physics-based models for simulating various sensors, most prominently a model for sensor types based on wave propagation, such as laser range finding devices. Application examples of the simulation framework are presented from the mobile robotics rough-terrain motion planning domain. Three novel rough-terrain planning algorithms are presented which are extensions of known approaches. To quantify the navigational difficulty on rough terrain, a new generic measure named "obstacleness" is proposed which forms the basis of the proposed algorithms. The first algorithm is based on Randomised Potential Field Planners (RPP) and consequently is a local algorithm. The second proposed planner extends RRTconnect , a bi-directional Rapidly Exploring Random Tree (RRT) algorithm and biases exploration of the search space towards easily traversable regions. The third planner is an extension of the second approach and uses the same heuristic to grow a series of additional local RRTs. This allows it to plan trajectories through complex distributions of navigational difficulty benefitting from easy regions throughout the motion plan. A complete example is shown in which the proposed algorithms form the basis for sensor-based dynamic re-planning simulated in the presented framework. In the scenario, a simulated planetary rover navigates a long distance over rough terrain while gathering sensor data about the terrain topography. Where obstacles are sensed which interfere with the original motion plan, dynamic re-planning routines are applied to circumnavigate the hindrances. In the course of this document a complete simulation environment is presented by means of a theoretical background and application examples which can significantly support the development of robot motion planning algorithms. The framework is capable of simulating setups which fulfil the requirements posed by stateof-the-art motion planning algorithm development.

EPFL2006

Bidirectional transformation between BIP and SysML for visualisation and editing

Leandro Kieliger, Clément Jean Maurice Nussbaumer

When it comes to designing software, the classic procedure consists of writing code that complies with the projects requirements first, and then to extensively test for bugs and defects. Although this approach is valid and can produce correct results, it is both time consuming and error prone. Moreover, depending on the time of detection, errors can turn out to be very difficult to correct. Model-based design however allows for verification prior to the coding task. The component-based approach allows to master complexity by structuring systems hierarchically into sub-components where each of them can be designed and validated individually. Despite this approach leading to an increased initial cost of development, it has the significant advantage of detecting and correcting problems early in the life cycle of a project, when errors are relatively inexpensive to fix. Using the BIP framework and its semantics, it is possible to develop models which are correct by construction. This further reduces testing and validation costs. In this project we experimented the possibility of visually expressing the structure of a BIP model in a modeling language. We call this conversion the forward transformation while modification of the BIP code upon changes made to the SysML model is called the backward transformation. The results are illustrated by two transformations: one, done step-by-step, for a relatively simple BIP model and one, more complex, which contains nested components and which was used in the context of the CubETH project.

2017

RFID seeking: Finding a lost tag rather than only detecting its missing

Qiang Wang, Lei Xie, Jian Xu, Chen Zhang

This paper proposes a novel type of RFID application, i.e., RFID seeking. Several existing types of RFID applications such as monitoring, searching, locating/navigating, are similar with RFID seeking. However, they are either inapplicable or vulnerable for RFID seeking scenarios, in which a user is to find a lost tagged item in a blind spot, or to find a wanted item among a mass of similar ones. In this paper, detailed requirements for RFID seeking are suggested. The first secure RFID seeking protocol is proposed, meeting all the given requirements. Its security is formally verified by using the AVISPA tool. The proposed protocol is server-less, lightweight, privacy-friendly to both RFID readers and tags, and is secure against common attacks such as eavesdropping, manipulating, replaying, tracing, Denial of Service (DoS), etc.

Elsevier2014

Rigid body dynamics simulation for robot motion planning

Alan Ettlin

EPFL2006

Rigid body dynamics simulation for robot motion planning

Bidirectional transformation between BIP and SysML for visualisation and editing

RFID seeking: Finding a lost tag rather than only detecting its missing

A usage scenario for a piece of software; often used in the plural to suggest situations where a piece of s

RFID seeking: Finding a lost tag rather than only detecting its missing

Rigid body dynamics simulation for robot motion planning

Bidirectional transformation between BIP and SysML for visualisation and editing