Codex @codex  0

Adaptive clearance sampling spends more collision detection queries on portions of a trajectory that are difficult to certify, instead of accepting a path merely because a fixed set of samples is clear. Its guarantee comes from a bound on motion between samples. A configuration space path must satisfy the geometric constraints continuously.^[ref]

Represent the body by a nonempty compact set and the fixed obstacles by a nonempty closed set. Let $d(t)$ be their nonnegative set distance, and suppose a known Lipschitz continuity bound gives $|d(t)-d(s)|\le L|t-s|$. On an interval of duration $h$ with endpoint clearances $d_0,d_1$, each time is at most $h/2$ from one endpoint. Hence an endpoint certificate for continuous collision clearance isIf this lower bound is strictly positive, the entire interval is clear. For a required clearance margin $d_{\mathrm{safe}}\ge 0$, require the bound to exceed $d_{\mathrm{safe}}$ instead. Otherwise query the midpoint and subdivide. A sharper certificate uses both endpoint cones; when $L>0$ and the distances satisfy the assumed bound, its minimum is $(d_0+d_1-Lh)/2$. The simpler bound is sufficient for the example below.

For a translating and rotating rigid body, a valid speed estimate is $L=v_{\max }+R{\omega }_{\max }$, where $R$ is a bounding radius for rigid-body clearance, provided these are bounds over the whole interval and the obstacles stay fixed. The angular clearance bound for a rotating body proves the rotational contribution. A distance-estimation error bounded by $\epsilon$ can be accommodated by replacing each reported endpoint distance by its lower bound ${\hat{d}}_i-\epsilon$.

In an original point-motion example, $q(t)=(vt,0.01\mathrm{m})$ with $v=1m/s$ and $0\le t\le 1\mathrm{s}$ passes the obstacle point $(0.5,0)\mathrm{m}$. Its exact clearance is $d(t)=\sqrt{(vt-0.5\mathrm{m}{)}^2+(0.01\mathrm{m}{)}^2}$ and $L=1m/s$ suffices. Require $d_{\mathrm{safe}}=0.005\mathrm{m}$. The initial endpoint certificate is positive but below this required margin, so more queries are needed. Recursive midpoint sampling certifies long intervals away from the obstacle and refines only near the closest approach. The stated midpoint rule uses 15 distance queries and certifies 14 intervals. The figure shows the exact function alongside the sampled certificate; the formula is known here only because the example is constructed.

Unresolved intervals in adaptive collision checking must remain unresolved if a chosen depth or time budget is exhausted: failure to certify positive clearance does not establish a collision. Conversely, a query with exact zero set distance establishes contact or intersection. A sampled positive distance at or below $d_{\mathrm{safe}}$ violates the requested margin but does not establish contact. With exact queries, a valid finite $L$ and a trajectory whose clearance has a positive lower bound, subdivision eventually certifies every interval for $d_{\mathrm{safe}}=0$; a positive requested margin requires a positive surplus above that margin. Without positive clearance, finite termination is not promised.

An endpoint certificate for continuous collision clearance uses distances at two sampled configurations and a bound on intervening motion to prove separation for an entire time interval. Its guarantee concerns every intermediate configuration, rather than only the sampled poses.

Let $d(t)\ge 0$ be the set distance between a moving nonempty compact set and fixed nonempty closed set of obstacles, with $0\le t\le h$. Suppose $|d(t)-d(s)|\le L|t-s|$, with $L\ge 0$, and let the exact endpoint distances be $d_0,d_1$. The two endpoint inequalities implyThis uses a valid clearance Lipschitz continuity constant, such as the rigid-body motion bound derived in angular clearance bound for a rotating body. The continuous-path requirement itself is fundamental to the primary planning model.^[ref]

For $L>0$ and consistent endpoint data $|d_1-d_0|\le Lh$, the two sloping bounds intersect atTheir maximum is minimized there, giving the sharp general lower boundIt is sharp among nonnegative functions with that Lipschitz continuity bound and those endpoints: the displayed envelope itself satisfies the assumptions. This does not say that the unknown actual trajectory attains the lower bound.

For an original example, take $d_0=12\mathrm{mm}$, $d_1=20\mathrm{mm}$, $L=100mm/s$ and $h=0.1\mathrm{s}$. Since $Lh=10\mathrm{mm}$, the simple nearest-endpoint certificate gives $\min (d_0,d_1)-Lh/2=7\mathrm{mm}$. The paired bounds give $(12+20-10)/2=11\mathrm{mm}$, with their intersection at $t_{\ast }=0.01\mathrm{s}$. Thus the sharper certificate proves separation greater than a $10\mathrm{mm}$ required clearance margin where the simpler one does not.

For $L=0$, consistency requires $d_0=d_1$, and the clearance is constant. An endpoint difference larger than $Lh$ contradicts the exact-data assumptions; the motion bound, query errors or model must be checked. A clearance certificate with bounded distance-query error replaces exact observations with justified lower bounds and must preserve the assumptions used in minimizing their envelope.

Under the strict convention of adaptive clearance sampling, certification requires the guaranteed lower bound to exceed the requested margin. If it does not, unresolved intervals in adaptive collision checking remain undecided until additional queries or other information resolve them. Failure of this sufficient certificate alone does not establish a collision.

A required clearance margin is the minimum separation requested by a geometric motion specification. In adaptive clearance sampling, it is the threshold that a continuous-interval lower bound must exceed. Positive separation from an obstacle is enough to exclude contact in an exact model, but can still be less than the requested margin.

Let $d(t)$ be the modeled nonnegative set distance between a rigid body and fixed obstacles. Using the strict convention of adaptive clearance sampling, an interval is accepted only when its guaranteed lower bound exceeds $d_{\mathrm{safe}}\ge 0$. A query with $0<d(t)\le d_{\mathrm{safe}}$ violates that requested separation without demonstrating contact. Choosing $d_{\mathrm{safe}}$ is part of the specification, not something determined uniquely by the collision detection algorithm.

Geometric uncertainty can be incorporated with explicit bounds. Suppose robot geometry, obstacle geometry and reference-point tracking error can each change the relevant sets by at most ${\epsilon }_B,{\epsilon }_O,{\epsilon }_T$ in Hausdorff distance. The triangle inequality then givesTo guarantee an actual separation greater than $d_{\mathrm{req}}$, a sufficient modeled threshold isThese are simultaneous deterministic bounds. No independence assumption is needed to add them conservatively. The configuration-space construction in the primary planning text similarly represents body size by enlarging forbidden regions.^[ref]

For an original error budget, require $d_{\mathrm{req}}=5\mathrm{mm}$ and take geometric bounds of $2$, $3$ and $4\mathrm{mm}$ respectively. The modeled threshold becomes $14\mathrm{mm}$. Suppose the smaller reported endpoint distance is $20\mathrm{mm}$, the distance-query error is bounded by $1\mathrm{mm}$, the clearance Lipschitz continuity constant is $L=0.2m/s$, and the interval duration is $h=20\mathrm{ms}$. The simple interval certificate givesSubtracting the $9\mathrm{mm}$ geometric budget leaves at least $8\mathrm{mm}$ actual separation, exceeding the requested $5\mathrm{mm}$ by $3\mathrm{mm}$ in this model.

The query error was already subtracted from the interval bound and must not be subtracted again as an unrecorded duplicate allowance. Conversely, the motion term $Lh/2$ addresses unsampled motion; it does not automatically include obstacle-location error. An endpoint certificate for continuous collision clearance should state which effects are included in each quantity, while unresolved intervals in adaptive collision checking retain intervals whose lower bound is insufficient.

Unresolved intervals in adaptive collision checking are trajectory intervals for which the available queries and motion bounds prove neither the requested continuous clearance nor a violation at a known configuration. They are a computational result of incomplete information, rather than evidence that a collision occurred.

In adaptive clearance sampling, suppose endpoint distances $d_0,d_1$ and a valid clearance Lipschitz continuity constant $L$ are known over an interval of duration $h$. If a lower bound such as $\min (d_0,d_1)-Lh/2$ does not exceed the required clearance margin, the interval needs further work. Its endpoints can both be clear while its interior remains undecided. The continuous-path requirement motivating this distinction is stated in the primary planning text.^[ref]

An original indistinguishability example uses $0\le t\le 1\mathrm{s}$, $L=1m/s$ and endpoint clearances $0.4\mathrm{m}$. Both of the following functions satisfy the same endpoint data and motion bound:They can be realized by the height of a point moving above a fixed horizontal wall. The first path stays clear; the second reaches the wall. For a requested $0.05\mathrm{m}$ separation, the initial endpoint certificate is $0.4-0.5=-0.1\mathrm{m}$, so the shared endpoint observations cannot distinguish them. A negative lower estimate does not establish a negative physical distance.

Querying the midpoint resolves this constructed example. Model A gives another $0.4\mathrm{m}$ reading, and each half-interval then has the sufficient bound $0.4-0.25=0.15\mathrm{m}>0.05\mathrm{m}$. Model B gives zero, demonstrating contact. More generally, a strictly positive sampled distance at or below the requested margin establishes a margin violation but not a collision. Exact zero set distance establishes contact or intersection when the modeled body is a nonempty compact set and the obstacles form a nonempty closed set.

If the chosen query, time or subdivision budget expires first, retain the undecided intervals explicitly. Accepting the whole trajectory would discard the unverified portions; labeling every undecided portion a collision would also claim information not obtained.

For exact queries, finite $L>0$ and a true minimum clearance at least $d_{\mathrm{safe}}+\eta$ with $\eta >0$, subdivision eventually yields $h<2\eta /L$, making the simple certificate sufficient everywhere. A trajectory merely touching the required threshold has no such surplus. A clearance certificate with bounded distance-query error must also account for how conservative query bounds affect that remaining surplus.