Multi-Robot Path Planning Visualizer

A Qt-based visualizer for Continuous Multi-Agent Path Finding (MAPF) algorithms. Renders agent movements with smooth trajectories in continuous 2D space.

Implementation

Built with Qt 4.6.1+ and C++17, the visualizer consists of:

Map Renderer: Parses and displays 2D grid maps with obstacles
Trajectory Parser: Reads timestamped agent positions from XML files
Animation Engine: Interpolates between waypoints for smooth continuous motion using Qt timers
Collision Visualization: Highlights agent positions and paths in real-time

The core rendering loop updates agent positions based on timestamps, supporting variable agent radii and dynamic obstacle visualization.

Compatible MAPF Algorithms

This visualizer supports any Continuous MAPF solver that outputs timestamped trajectories, including:

Continuous-CBS (CCBS) - Conflict-Based Search for continuous time
SIPP (Safe Interval Path Planning) - with time-continuous extensions
PBS (Priority-Based Search) - continuous variants
EECBS - Enhanced Explicit Estimation CBS
Any custom solver that outputs: agent ID, (x, y) positions, timestamps, and optional orientations

Simply convert your solver’s output to the XML format (see DemoInput/ for schema).

Requirements

Qt 4.6.1+ (Qt5/6 compatible with minor changes)
C++17 compiler
Qt Creator (recommended)

Build & Run

In the project root directory:

qmake
make
./ContinuousMAPFVisualizer

Or open the .pro file in Qt Creator and run directly.

Usage

Launch the application
Load XML scenario file: File → Open (examples in DemoInput/)
Control playback with play/pause/speed controls
Adjust visualization settings (agent size, trail length, etc.)

Input Format

XML schema includes:

<map>: grid dimensions, obstacle positions
<agents>: agent IDs, start/goal positions
<trajectory>: timestamped (t, x, y, θ) waypoints for each agent

Example:

<scenario>
  <map width="32" height="32">...</map>
  <agents>
    <agent id="0" start_x="1" start_y="1" goal_x="30" goal_y="30"/>
  </agents>
  <trajectory agent_id="0">
    <waypoint t="0.0" x="1.0" y="1.0" theta="0.0"/>
    <waypoint t="1.5" x="2.3" y="1.8" theta="0.4"/>
    ...
  </trajectory>
</scenario>

See DemoInput/*.xml for complete examples.

Credits

Framework inspired by Continuous-CBS
Benchmark maps from MovingAI

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