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Gathering

Robots must meet at a single point that is not fixed in advance, and stay there.

Problem statement and measuresexpand

\(n\) robots start at distinct points and must all reach the same point in finite time and remain there. For \(n = 2\) the problem is called rendezvous. Time is counted in rounds (FSYNC, SSYNC) or in epochs (ASYNC: intervals in which every robot completes at least one full Look–Compute–Move cycle); colours count light colours.

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).

Byzantine faults, FSYNC

verified
Time: unknownColours: tight

In FSYNC, gathering tolerates \(f\) Byzantine robots when \(n \ge 3f+1\).

Assumed (added on the last edge are outlined)

+Bodypoint robots+Visibilityunlimited+Opacitytransparent: every robot sees every robot within range+Schedulerfully synchronous (FSYNC)+Number of robots\(n \ge 3\)

Not assumed

Faultsup to \(f\) Byzantine robotsLights (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: unlimited visibility
A robot sees all robots (subject to opacity).
Opacity: transparent
Robots do not obstruct each other's view.
Faults: Byzantine
Up to \(f\) robots move arbitrarily (adversarially); with lights, they may also set arbitrary colours.
Scheduler: FSYNC
FSYNC: every robot executes one atomic cycle in every round.
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.
Number of robots: \(n \ge 3\)
\(n\ge 3\) robots.

What is known

Time · rounds (FSYNC, SSYNC) or epochs (ASYNC) until the task is done; "finite" when only solvability is known
unknown
Whether \(3f+1\) is necessary is open.
lower boundnone known
introductory—
current best
\(\text{finite}\)
\(n \ge 3f+1\)common chiralitya Look returns a multiset (multiplicities are seen)
Colours · colours of the light per robot (0 for oblivious robots)
tight
No colours.
lower boundnone known
introductory—
current best
\(0\)
\(n \ge 3f+1\)common chiralitya Look returns a multiset (multiplicities are seen)

Results, in order of publication

Agmon & Peleg 2006 current best
Time \(\text{finite}\)Colours \(0\)
\(n \ge 3f+1\)common chiralitya Look returns a multiset (multiplicities are seen)

Introductory and current best (Theorem 5.10, with \(n \ge 3f+1\)); \(n=3\) tolerates \(f=1\) (Theorem 5.3). Checked against the full text.

Open questions

None recorded for this variant.

Notes

Défago et al. study self-stabilizing gathering under crash or Byzantine faults (Distributed Computing 2020; bounds not checked).

What carries over from neighbouring settings

Read off the order of assumptions, not checked case by case: results may carry extra assumptions (shown on their pages), and asynchronous time is measured in epochs.

Algorithms from weaker settings work here

Lower bounds from stronger settings hold here

No catalogued stronger setting.

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