Library (computing) | EPFL Graph Search

In computer science, a library is a collection of non-volatile resources used by computer programs, often for software development. These may include configuration data, documentation, help data, message templates, pre-written code and subroutines, classes, values or type specifications. In IBM's OS/360 and its successors they are referred to as partitioned data sets. A library is also a collection of implementations of behavior, written in terms of a language, that has a well-defined interface by which the behavior is invoked. For instance, people who want to write a higher-level program can use a library to make system calls instead of implementing those system calls over and over again. In addition, the behavior is provided for reuse by multiple independent programs. A program invokes the library-provided behavior via a mechanism of the language. For example, in a simple imperative language such as C, the behavior in a library is invoked by using C's normal function-call. What d

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

Optimizing Higher-Order Functions in Scala

Iulian Dragos

Scala relies on libraries as the default mechanism for language extension. While this provides an elegant solution for growing the language, the performance penalty incurred by call-by-name parameters, boxing and anonymous functions is high. We show that inlining alone is not enough to remove this overhead, and present a solution based on decompilation of library code combined with inlining, dead code elimination, and copy propagation. We evaluate our approach on two language extensions, Java-like assert and C-like for-loops and show improvements of up to 45%.

2008

Detailed heap profiling

Stuart Anthony Byma, James Richard Larus

Modern software systems heavily use the memory heap. As systems grow more complex and compute with increasing amounts of data, it can be difficult for developers to understand how their programs actually use the bytes that they allocate on the heap and whether improvements are possible. To answer this question of heap usage efficiency, we have built a new, detailed heap profiler called Memoro. Memoro uses a combination of static instrumentation, subroutine interception, and runtime data collection to build a clear picture of exactly when and where a program performs heap allocation, and crucially how it actually uses that memory. Memoro also introduces a new visualization application that can distill collected data into scores and visual cues that allow developers to quickly pinpoint and eliminate inefficient heap usage in their software. Our evaluation and experience with several applications demonstrates that Memoro can reduce heap usage and produce runtime improvements of 10%.

ACM2018

Rigid body dynamics simulation for robot motion planning

Alan Ettlin

EPFL2006