Mobility Matters
Home›Mobile robots in the plane›Formation problems›Pattern formation›k-grouping›Gathering›Near-gathering

Near-gathering

Robots must get within a small distance of each other without ever colliding.

Problem statement and measuresexpand

Robots with limited visibility, each seeing only the robots within its visibility radius \(V\), start at distinct points whose visibility graph (two robots joined by an edge when they are within distance \(V\)) is connected. They must reach a configuration in which every robot sees all others, without a collision (two robots at the same point) ever happening.

Measures: Time, rounds (FSYNC, SSYNC) or epochs (ASYNC) until the task is done; "finite" when only solvability is known; Colours, colours of the light per robot (0 for oblivious robots).

SSYNC, limited visibility, disoriented

verified
Time: tightColours: tight

Disoriented robots near-gather in \(O(\Delta_0^2)\) epochs in SSYNC.

Assumed (added on the last edge are outlined)

+Bodypoint robots+Opacitytransparent: every robot sees every robot within range+Faultsno faults+Schedulersemi-synchronous (SSYNC)

Not assumed

Visibilitylimited: robots see only within a fixed radiusLights (persistent memory)oblivious, no light (OBLOT)Agreement on coordinatesno agreement on local coordinate systemsMovementnon-rigid: the adversary may stop a move after some minimum distance \(\delta\)Multiplicity detectionnone: a point with several robots looks like one robotRandomnessdeterministicIdentifiersanonymous: all robots are identical
Formal definitions of this setting
Body: point
Each robot is a point of the plane: several robots may share a point (multiplicity), and a robot hides only what lies exactly behind it on a line of sight.
Visibility: limited visibility
A robot sees exactly the robots within Euclidean distance \(V\) of its position, for a fixed radius \(V>0\).
Opacity: transparent
Robots do not obstruct each other's view.
Faults: no faults
All robots follow the algorithm forever.
Scheduler: SSYNC
SSYNC: time is divided into rounds; in each round a non-empty subset of robots, chosen by a fair adversary, executes one atomic Look–Compute–Move cycle. Called Atom by Prencipe Prencipe 2007.
Lights (persistent memory): oblivious
OBLOT: a robot's computation depends only on the current snapshot; nothing persists across cycles.
Agreement on coordinates: disoriented
Each robot \(r\) observes in its own coordinate system, obtained from the global one by an unknown similarity (translation, rotation, uniform scaling, and possibly reflection); systems may differ between robots and, in some models, between cycles. Papers that call robots disoriented do not always mean this: Défago and Souissi use the word while assuming chirality Défago & Souissi 2008. Some papers also let the adversary change a robot's rotation, reflection and unit at every Look (variable disorientation) Flocchini et al. 2023 Masuzawa et al. 2026.
Movement: non-rigid
In a Move phase the adversary may stop a robot before its destination, but only after it has travelled at least \(\delta>0\) (a constant unknown to the robots) or reached the destination.
Multiplicity detection: no multiplicity detection
A snapshot is a set of points: a point occupied by several robots looks like a single robot.
Randomness: deterministic
The destination computed in a cycle is a function of the snapshot (and the light, if any).
Identifiers: anonymous
Robots are indistinguishable and run the same algorithm.

What is known

Time · rounds (FSYNC, SSYNC) or epochs (ASYNC) until the task is done; "finite" when only solvability is known
tight
Within contracting protocols.
lower bound
\(\Omega(\Delta_0^2)\) Castenow et al. 2022
bottlenecklocality
holds when
  • only for \(\lambda\)-contracting protocols
introductory—
current best
\(O(\Delta_0^2)\)
Colours · colours of the light per robot (0 for oblivious robots)
tight
No colours.
lower boundnone known
introductory—
current best
\(0\)

Results, in order of publication

Time \(O(\Delta_0^2)\)Colours \(0\)

Theorem 18; first near-gathering protocols for disoriented robots.

Open questions

  1. Near-gathering in \(O(\Delta_0)\) epochs?

Know a better result for this setting, or found a mistake? Suggest a result · Report an error. Accepted contributions are acknowledged.