A spatial view of allocation
The first animation shows four robot positions, local feasible regions, and the mass center. Its objective measures the sum of displacements from the initial locations, with a dashed optimal-cost reference.
Simulation study / MULTI-AGENT OPTIMIZATION
Distributed Task Allocation.
Local motion, collective structure.
Four-agent simulation studies visualize position updates, spatial constraints, and the evolving group configuration.
- Distributed optimization
- Four-agent simulation
- Task allocation
01 / OVERVIEW
The idea.
These presentation simulations follow four agents as their positions evolve within a shared task. The animations make the spatial configuration visible over time, including a lifting-related allocation study and a second comparison shown in parallel panels.
- Four agents shown throughout
- Spatial configurations and trajectory traces
- Original axes and legends retained
ROBOTICS IN MOTION · 22 sec
Four agents, one allocation.
Original presentation simulation. This animation shows a four-agent allocation study; it is presented separately from the published lifting-paper experiments.
ROBOTICS IN MOTION · 30 sec
Two allocation scenarios.
An excerpt from the original two-panel presentation simulation. Axes, legends, and trajectories are retained.
02 / DEMONSTRATION
Inside the demo.
- Initialize
The four agents start from their displayed positions.
- Update
The agents move as the simulated allocation evolves.
- Inspect
The traces and final configuration reveal the resulting arrangement.
Two views of convergence
The second animation compares two four-agent cases. Each panel shows positions, total cost, and pairwise distances d12, d13, and d14 against the distance limit dmax.