Consider a two-dimensional random walk, but this time the probabilities are not 1/4, but some values p_1, p_2, p_3, p_4 with $\sum_{i=1}^4 p_i=1$. For example, from (0,0), it goes to (1,0) with p_1, goes to (0,1) with p_2 etc.
The question is how to compute the probability x of going back to (0,0), starting from (0,0). In general, this probability is not 1.
Thanks.
Since the number of visits has geometric distribution, it's enough to find its expected value.
Here is one approach: since you can solve the one-dimensional case, treat the two-dimensional case as two "interleaved" one-dimensional walks, one north-south, the other east-west. Let's say $p_1$ is the probability of north, $p_2$ is the probability of south. Then at each step, we do a step from the north-south walk with probability $p_1+p_2$ and a step from the east-west walk with probability $p_3+p_4$; each step of the north-south walk is north with probability $p_1/(p_1+p_2)$ and south with probability $p_2/(p_1+p_2)$.
So then the probability of being back at the origin at time $N$ is the sum over $m$ of
$P(X=m) P(\text{north-south walk at 0 after $m$ steps})P(\text{east-west walk at 0 after $N-m$ steps})$
where $X$ is Binomial$(N, p_1+p_2)$.
Sum over $N$ to get the total expected number of visits.
I don't see that this will give you a closed-form answer, but it may at least make it easier to compute and/or obtain bounds.
A special case where we can avoid one of the two sums in James Martin's answer is when the "determinant" $p_1p_3-p_2p_4$ of the four probabilities is zero. Then we can treat the random walk as a "sum" of two independent one-dimensional random walks, one taking steps $(+1/2, +1/2)$ or $(-1/2,-1/2)$, the other taking steps $(+1/2,-1/2)$ or $(-1/2,+1/2)$. The original walk is back at the origin precisely when both these 1D-walks are.
If the transition probabilities of the two component walks are $p, (1-p)$ and $q, (1-q)$ respectively, then the expected number of visits to the origin (including the start) is $$\sum_{n=0}^\infty \binom{2n}{n}^2 p^nq^n(1-p)^n(1-q)^n.$$
In terms of the original probabilities, $$pq(1-p)(1-q) = (p_1+p_2)(p_2+p_3)(p_3+p_4)(p_4+p_1).$$
I'm no expert on this type of sum, but according to Maple, $$\sum_{n=0}^\infty \binom{2n}{n}^2 x^n = \frac2{\pi} EllipticK(4\sqrt{x}).$$
The probability of never returning is the reciprocal of this (with $x=pq(1-p)(1-q)$), in other words $$\frac{\pi}{2EllipticK(4\sqrt{(p_1+p_2)(p_2+p_3)(p_3+p_4)(p_4+p_1)})}.$$
An obvious question is whether this holds also when $p_1p_3 \neq p_2p_4$. Off the top of my head I don't see why it couldn't.
