This Thesis considers the use of a team of multimodal robots capable of switching between aerial and terrestrial locomotion modes in wilderness search and rescue. It presents a novel search planning method that coordinates the robots to maximize the probability of locating a mobile target in the wilderness, potentially, last seen on an a priori known hiking trail. It has two major components:​ (i) target-motion prediction, and (ii) probability-guided multimodal robot search-trajectory generation. In the former subproblem, the formulation of 3D probability curves captures target distributions under the influence of a priori known trails. In the latter, the use of a tree structure represents decisions involved in multimodal probability-curve-guided search planning, which enables simultaneous optimization of trajectory generation and mode selection. Through simulations, it has been demonstrated that multimodal robotic search teams, coordinated via the trajectory planning method presented, clearly outperform their unimodal counterparts in terms of search success rates.