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SLAMBench for Android Build Status

This repository contains the Android version of SLAMBench. SLAMBench for Android uses the KinectFusion algorithm to evaluate the CPU (and the GPU) performance of mobile phones.

Related Papers

B. Bodin, L. Nardi, M. Z. Zia, H. Wagstaff, G. S. Shenoy, M. Emani, J. Mawer, C. Kotselidis, A. Nisbet, M. Lujan, B. Franke, Paul H. J. Kelly, M. O’Boyle. Integrating algorithmic parameters into benchmarking and design space exploration in dense 3D scene understanding. In Intl. Conf. on Parallel Architectures and Compilation Techniques (PACT 2016), Haifa, September 2016.

L. Nardi, B. Bodin, M. Z. Zia, J. Mawer, A. Nisbet, P. H. J. Kelly, A. J. Davison, M. Luján, M. F. P. O’Boyle, G. Riley, N. Topham, and S. Furber. Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM. In IEEE Intl. Conf. on Robotics and Automation (ICRA 2015), Seattle, Washington USA, May 2015.

More informations

About the benchmark algorithm

KinectFusion is a Simultaneous Localization And Mapping algorithm (SLAM) and it uses an RGB-D sensor (like the XBox Kinect).

SLAM algorithms are used:

RGB-D sensors are :

We are using the SLAMBench implementation (C++,OpenMP,OpenCL) of this algorithm, which itself is inspired from the KFusion implementation (CUDA only). SLAMBench is a framework which includes speed, accuracy and power measurement.

About the study

Many vendors include OpenCL in their mobile devices to use the GPUs for computation, and this provides opportunities for real-time vision applications. Vendors also started to integrate RGB-D sensor in their devices, we investigate if KinectFusion is a suitable solution for mobile devices with or without OpenCL.

About the configurations

KinectFusion can be parametrized, but its default configuration is too slow to run on any mobile phones (even the most powerful one). We are using custom configurations (called fast1 to fast4) which make possible to run KinectFusion on these mobile phones.

How to compile it

Well, there is no standard procedure yet, but here is a way...

Quick compilation

Just a make should work, but please read the preparation before.

Preparation

I prepared it on a clean Fedora 24 Workstation, and this is what I did first :

  dnf install java-1.8.0-openjdk java-1.8.0-openjdk-devel 
  dnf install python
  dnf install gcc gcc-c++

  dnf install libstdc++-devel.i686 zlib.i686

  wget https://dl.google.com/dl/android/studio/ide-zips/2.1.2.0/android-studio-ide-143.2915827-linux.zip
  unzip android-studio-ide-143.2915827-linux.zip
  mkdir -p ~/.local/Android/
  mv android-studio ~/.local/Android/android-studio
  ~/.local/Android/android-studio/bin/studio.sh

  wget https://dl.google.com/android/android-sdk_r24.4.1-linux.tgz
  tar xzf android-sdk_r24.4.1-linux.tgz
  mv android-sdk-linux ~/.local/Android/Sdk
  ~/.local/Android/Sdk/tools/android list sdk --all
  ~/.local/Android/Sdk/tools/android update sdk -u -a -t "platform-tools,tools,android-23,build-tools-23.0.2,extra-android-m2repository,addon-google_apis-google-23"

or just type make sdk.

  wget http://dl.google.com/android/repository/android-ndk-r12b-linux-x86_64.zip
  unzip android-ndk-r12b-linux-x86_64.zip
  mv android-ndk-r12b ~/.local/Android/android-ndk-r12b

or just type make ndk.

Then you need to fix the absolute paths in ./local.properties:

echo "sdk.dir=/home/`whoami`/.local/Android/Sdk" > ./local.properties
echo "ndk.dir=/home/`whoami`/.local/Android/android-ndk-r12b" >> ./local.properties

Compilation

Just a make should work.

Installation

Once the apk is built, you can install it on a mobile phone using the following command :

adb install ./app/build/outputs/apk/app-debug.apk

Know errors

> Failed to apply plugin [id 'com.android.application']
   > Minimum supported Gradle version is ???? If using the gradle wrapper, try editing the distributionUrl in gradle-wrapper.properties to gradle-2.14.1-all.zip

If this error occurs the best is to do as recommanded, just update the gradle-wrapper.properties file.