Ausarbeitung/wiselib.tex

   1 \section{Wiselib}
   2 The \definition{Wiselib}\cite{wiselib} is a C++ algorithm library for
   3 sensor networks, containing for example algorithms for routing, localization and
   4 time synchronization, and is strongly focused on portability and cross-platform
   5 development. In particular, it allows the user to develop applications that run
   6 on different hardware platforms without the need to change the code, and it
   7 strongly uses C++ templates to achieve that feature. Amongst the supported
   8 platforms are diverse sensor node platforms, like iSense, Contiki and TinyOS,
   9 but there are as well implementations for the diverse x86-compatible Personal
  10 Computer platforms, and the Shawn sensor network simulator.
  11
  12 \subsection{Architecture}
  13 \paragraph{Concepts and Models}
  14 Wiselib makes strong uses of \definition{concepts} and \definition{models} as
  15 central design objects. Concepts serve as an informal description of interfaces,
  16 only existent in documentation, defining expected parameters and types. Models
  17 however implement these interfaces in C++ code while fulfilling their
  18 specification. The Wiselib algorithms can in turn rely on the concepts as a
  19 generic specification, and take models as template parameters to use their
  20 functionality, so a function call will be immediately resolved to a specific
  21 model at compile time without the need for an additional function call as it is
  22 the case with virtual inheritance. Furthermore, this also allows usage on
  23 platforms which do not have support for C++, as the bytecode generated by the
  24 compiler does not include C++ specific extensions (no virtual function tables,
  25 and templates are resolved at compile time) and can be linked against any
  26 Standard C Library.
  27
  28 This makes cross-platform development easily possible. For example, to implement
  29 a routing algorithm, one can rely on the concept of a Radio to send and receive
  30 data packets, without needing to implement code specific to the used radio
  31 hardware. The users of that routing algorithm can now choose which radio model
  32 they want to use, according to their needs and the underlying hardware, provided
  33 that their radio model also implements the same Radio concept that the routing
  34 algorithm uses.
  35
  36 \begin{figure}
  37   \centering
  38   \includegraphics[width=.8\textwidth]{images/Wiselib-Arch.pdf}
  39   \caption{Wiselib architecture\label{fig:wiselib-arch}}
  40 \end{figure}
  41 Besides algorithms, and basic concepts and models, the Wiselib also consists of
  42 two other main parts: the internal interface and the external interface (see
  43 Figure~\ref{fig:wiselib-arch}).
  44
  45 \paragraph{External Interface}
  46 The \definition{External Interface} provides access to the underlying \ac{OS},
  47 like iSense, Contiki, Shawn\ldots and defines concepts like a Radio or a Timer.
  48 Thus, the concepts are as generic as possible to match all supported operating
  49 systems and provide a light-weight abstraction to the underlying \ac{OS}. These
  50 concepts sometimes extend the generic concepts, for example there is a TxRadio
  51 which has the ability to set the transmission power on the radio. The models
  52 (for example an iSenseRadioModel or a ShawnTimerModel) implement these concepts
  53 on the specific operating system, and can be passed around as template
  54 parameters.
  55
  56 \paragraph{Internal Interface}
  57 The \definition{Internal Interface} defines concepts and models for data
  58 structures that can be used in algorithms. This allows to specialize for
  59 restricted platforms; for instance a wireless sensor node without dynamic memory
  60 management can use a static implementation of lists and other containers,
  61 whereas a full-grown desktop can use the dynamic implementation provided by the
  62 C++ \ac{STL}. For this purpose, the Wiselib also contains the
  63 \acused{pSTL}\definition{pico Standard Template Library} (\acs{pSTL}) which
  64 implements a subset of the \ac{STL} without the use of dynamic memory
  65 allocation.
  66
  67 \paragraph{Stackability}
  68 Another central design principle used in the Wiselib is
  69 \definition{stackability}, which describes the possibility to stack
  70 implementations of the same concept, thereby building a layered structure. For
  71 example, one could stack a cryptography algorithm on top of a radio model, which
  72 both implement the Radio concept. In this case, the cryptography layer doesn't
  73 have to know anything at all about the underlying implementation, as long as it
  74 can use the Radio concept of the underlying layer. And it can even provide the
  75 same interface to a possibly higher layer in order to provide transparent packet
  76 de- and encryption over the radio.
  77
  78 \subsection{Roomba Control}
  79 Even more interesting is the fact that the Wiselib includes code to control an
  80 iRobot Roomba\index{Roomba} over a serial interface, and getting access to its
  81 internal sensor data, using the \ac{ROI}\index{Roomba Open Interface} mentioned
  82 earlier. For this purpose, it defines two concepts for Robot Motion:
  83
  84 \paragraph{TurnWalkMotion concept}\index{TurnWalkMotion (concept)}
  85 This concept represents a simple robot that can turn on the spot and walk
  86 straight, without automatic stopping.
  87 \begin{description}
  88   \item Types:
  89     \begin{description}
  90       \item[\code{velocity\_t}] Type for velocity measurement
  91       \item[\code{angular\_velocity\_t}] Type for angular velocity measurement
  92     \end{description}
  93   \item \todo{clearpage?} Methods:
  94     \begin{description}
  95       \item[\code{int turn(angular\_velocity\_t)}] turn the robot with a
  96         constant angular velocity
  97       \item[\code{int move (velocity\_t)}] move the robot straight with a
  98         constant velocity
  99       \item[\code{int stop()}] stop the robot
 100       \item[\code{int wait\_for\_stop()}] hold the execution until the robot has
 101         stopped
 102     \end{description}
 103 \end{description}
 104
 105 \paragraph{Odometer concept}\index{Odometer (concept)}
 106 This concept represents an Odometer which tracks motions over time.
 107 Whenever the object turns or moves, internal counters will adjust their
 108 guessing of the object's traveled distance and current orientation.
 109 \begin{description}
 110   \item Types:
 111     \begin{description}
 112       \item[\code{angle\_t}] Type for angle measurement
 113       \item[\code{distance\_t}] Type for distance measurement
 114     \end{description}
 115   \item Methods:
 116     \begin{description}
 117       \item[\code{angle\_t angle()}] return the current angle
 118       \item[\code{int reset\_angle()}] reset the angle of the object
 119       \item[\code{distance\_t distance()}] return the current distance
 120       \item[\code{int reset\_distance()}] reset the distance of the object
 121       \item[\code{int register\_state\_callback (T *obj)}] register a callback
 122         that gets called when the state changes
 123       \item[\code{int unregister\_state\_callback (int)}] unregister a
 124         previously registered callback
 125       \item[\code{int state()}] return the current state
 126     \end{description}
 127 \end{description}
 128
 129 \paragraph{ControlledMotion class}\index{ControlledMotion (class)}
 130 On top of the TurnWalkMotion and Odometer concepts builds the
 131 \textit{ControlledMotion}\index{ControlledMotion (class)} model. It takes
 132 implementations of each of these concepts as template parameters and extends the
 133 simple turn-and-walk paradigm by a temporal dimension, which let the robot stop
 134 after a specific time interval. In particular, it provides the following
 135 methods:
 136 \begin{description}
 137   \item[\code{int move\_distance(distance\_t, velocity\_t)}] move the robot
 138     straight by a given distance with a given velocity
 139   \item[\code{int turn\_about(angle\_t, angular\_velocity\_t)}] turn the robot
 140     about a given angle with a given angular distance
 141   \item[\code{int turn\_to(angle\_t, angular\_velocity\_t)}] turn the robot
 142     to a given orientation with a given angular distance
 143 \end{description}
 144
 145 The class first registers a callback function at the given Odometer instance,
 146 and then uses its distance and angle values to control the robot over the
 147 TurnWalkMotion instance. Everytime the state of the robot changes (i.~e. new
 148 data from its sensors are received), it compares the new actual values with the
 149 target values given by the user through the functions above, and if the actual
 150 values exceed the target values, the robot is stopped.
 151
 152 \paragraph{Underlying Roomba Implementation}
 153 The actual communication with the Roomba is done in the
 154 \textit{RoombaModel}\index{RoombaModel (class)} class. It implements the
 155 aforementioned TurnWalkMotion\index{TurnWalkMotion (concept)} and
 156 Odometer\index{Odometer (concept)} concepts and therewith allows the interaction
 157 with a ControlledMotion\index{ControlledMotion (class)} instance. In particular,
 158 it manages the serial communication with the Roomba and translates the function
 159 calls \code{turn()}, \code{move()} and \code{stop()} of the TurnWalkMotion
 160 concept to the according parameters for the \ac{ROI} \cmd{Drive} command, reads
 161 a subset of the Roomba's sensors and presents the sensor data to the user, and,
 162 while implementing the Odometer concept, calculates the covered distance and
 163 angle from the Roomba's right and left wheel rotations.
 164
 165 The sensor data is read from the Roomba using the \cmd{Stream} command on the
 166 \ac{ROI}, which results in a sensor data packet (see Section
 167 \ref{sec:roi-stream-packet}) every 15~ms, and $66.67$ packets per second. At a
 168 speed of 19,200 baud in mode \ac{8N1}, the maximum size of a data packet is
 169 $19,200 \div (66.67 \times 9) = 32$ byte, so at the moment only the sensor
 170 packets \emph{encoder counts left/right} (IDs~\magicvalue{0x2b},
 171 \magicvalue{0x2c}, 2+2 bytes), \emph{battery voltage/current/charge/capacity}
 172 (IDs~\magicvalue{0x16}, \magicvalue{0x17}, \magicvalue{0x19},
 173 \magicvalue{0x1a}, 2+2+2+2 bytes) are streamed, which add up to 18 data bytes +
 174 3 header/checksum bytes. There has currently been no success yet in
 175 communicating at the higher speed of 115,200 baud.
 176
 177 Also there has been research to use the distance and angle values that the
 178 Roomba itself provides (sensor packet~IDs \magicvalue{0x13} and
 179 \magicvalue{0x14}). However, according to the \ac{ROI} Specification these
 180 values are integer values, and the value is reset to zero every time it is read.
 181 By using the \cmd{Stream} command on the \ac{ROI} and therefore reading these
 182 values every 15~ms, the Roomba cannot move fast enough to increment these values
 183 to \magicvalue{1}, so everytime \magicvalue{0} is read. It is obvious that
 184 these sensor values are not suited for such rapid evaluations, and can only be
 185 used for larger distances and angles. Nevertheless, since the Wiselib Roomba
 186 control needs to keep track of the Roomba's current position and orientation as
 187 fast as possible to maintain a certain accuracy in movement, the distance and
 188 angle values as provided by the Roomba itself cannot be used. On the other hand,
 189 working with the Roomba's wheel encoder counts (sensor packet~IDs
 190 \magicvalue{0x2b} and \magicvalue{0x2c}) has proven itself quite acceptable.
 191 After a few test runs, the number of encoder counts per~mm for straight
 192 walks turned out as $2.27$, and for turning on the spot, $2.27 \times 115 =
 193 261.05$ encoder counts per radian, which is the number of encoder counts per~mm
 194 multiplicated with half the Roomba's wheelbase. So when new sensor data is read
 195 each 15~ms, the RoombaModel implementation calculates the Odometer
 196 \index{Odometer (concept)} distance and angle from these values.
 197
 198 \todo{cite Wisebed book chapter on Roomba code}