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Fluidic Body: Swarm Robots as a Fluid Extension of the Hand

Michikuni Eguchi, Shigeo Yoshida, Mai Nishimura, Takefumi Hiraki

November 2026

TL;DR Fluidic Body lets a person steer a tabletop robot swarm with one hand. The robots act as particles of a simulated fluid, and opening or closing the hand makes the swarm soft enough to flow around obstacles or hard enough to push objects. In a VR study, all 17 participants completed a combined avoid-and-push task, against 8 of 17 with an RVO baseline, in half the time.

What they do

Swarm interfaces usually let a person say where the robots should go, but not how the group should behave. Fluidic Body puts a simulated fluid between the hand and a tabletop swarm. Each robot is a particle of the fluid, and hand movements change the fluid’s viscosity and density. An open hand gives a soft swarm that deforms through gaps; a closed hand gives a hard, cohesive mass that pushes objects.

How it works

  • Controller. Smoothed particle hydrodynamics (SPH) gives each robot a fluid force (pressure plus viscosity). Inter-robot repulsion is added, plus a shape force that pulls robots into the target region along a Laplace potential field with no dead ends around obstacles.
  • Hand mapping. Hand shape switches between a soft setting (low viscosity and reference density) and a hard one. Hand height spreads the swarm, and the hand’s outline becomes the region the swarm fills.
  • Hardware. 30 mm two-wheeled robots localize themselves from patterns cast by an overhead projector. A Leap Motion tracker reads the hand, and commands update every 100 ms.

Results

  • Scripted simulation with 16 robots (50 trials each): the soft setting succeeds 98% on obstacle avoidance against 16% for RVO. The hard setting matches RVO’s 100% on transportation and is faster (36.1 vs 37.8 s).
  • VR user study (N=17), combined avoid-and-push task: 17/17 successes against 8/17 for RVO, in 38.5 vs 76.9 s. Workload is lower (NASA-TLX 30.3 vs 62.7) and agency higher (5.96 vs 3.97 of 7). The single-demand tasks show no significant differences.
  • 88 visitors at SIGGRAPH 2025 operated the physical swarm and rated agency 3.81 and body ownership 3.09 of 5.

Limitations

The physical demonstration was uncontrolled and had no baseline. Its most common complaint was latency, caused by the 100 ms radio link and robots that must turn before moving. The study tested only two discrete fluid settings, one baseline (RVO with fixed standard parameters) and 16 robots, all on a tabletop plane.

Figures

From Figure 1: Left: the hand defines a region of virtual fluid, and the robots fill it and arrange themselves into a...
From Figure 1: Left: the hand defines a region of virtual fluid, and the robots fill it and arrange themselves into a fluid body on the table. Right: hand movements change the fluid's properties; a soft formation (blue) flows around an obstacle, and a hard formation (red) pushes an object.
From Figure 2: System design. The hand's shape, height and outline, captured by a hand-tracking camera, set the fluid...
From Figure 2: System design. The hand's shape, height and outline, captured by a hand-tracking camera, set the fluid properties and the swarm area. The controller simulates the fluid with SPH and treats each robot as one of its particles, which changes the flexibility, shape and size of the swarm.
From Figure 7: VR user study results for the RVO baseline and the fluid controller in three environments: (a) success...
From Figure 7: VR user study results for the RVO baseline and the fluid controller in three environments: (a) success rate, (b) completion time, (c) NASA-TLX workload, (d) body ownership and (e) agency. The two controllers diverge most on the combined avoidance-and-transportation task.
From Figure 9: Real-world demonstration setup. (a) A user guides the robots around objects and into a pick-up zone. (...
From Figure 9: Real-world demonstration setup. (a) A user guides the robots around objects and into a pick-up zone. (b) Side view: a projector above the table localizes the robots, a camera beside it tracks the objects, and a hand-tracking camera on the table captures the hand from below.
Abstract

Swarm robots have attracted growing interest as a physical interface for human--computer interaction, since a swarm can reshape its formation to fit the objects and surroundings it works with. For a human operator, however, adapting the swarm's behavior remains difficult. Most existing methods require the user to specify where the swarm should go, and they offer no intuitive way to change the collective's behavior as each task demands. We present Fluidic Body, a system that lets a person operate a swarm of fluid-imitating robots as an extension of the hand. The system places a virtual fluid between the hand and the swarm, and the user adapts the swarm's behavior to each task by changing the fluid's properties through simple hand movements. When the user opens the hand, the swarm becomes soft enough to deform and flow around obstacles. Closing the hand turns it into a hard, cohesive body that can push objects. We evaluated the controller's performance and its operability in two simulation experiments and one demonstration with physical robots. First, our controller handled both obstacle avoidance and object transportation better than an existing method that behaves the same way in every task. Second, in a VR user study, 17 participants completed the combined avoidance-and-transportation task faster and more reliably than with that method. They also reported a lower workload and a stronger sense of agency. Finally, this experience carried over to physical robots in a real-world demonstration (88 participants). These results suggest that treating a swarm as a fluid, a material people already understand, allows a robot swarm to work as a deformable extension of the human body.

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