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There is a significant growth in autonomy level in off-road ground vehicles. However, unknown off-road environments are often challenging due to their unstructured and rough nature. To find a path that the robot can move smoothly to its destination, it needs to analyse the surrounding terrain. In this paper, we present a hybrid terrain traversability analysis framework. Semantic segmentation is implemented to understand different types of the terrain surrounding the robot; meanwhile geometrical properties of the terrain are assessed with the aid of a probabilistic terrain estimation. The framework represents the traversability analysis on a robot-centric cost map, which is available to the path planners. We evaluated the proposed framework with synchronised sensor data captured while driving the robot in real off-road environments. This thorough terrain traversability analysis will be crucial for autonomous navigation systems in off-road environments.

The dynamics of a modern aircraft at high angles of attack is complicated, with hazardous phenomena such as wing rock, stall, and spin. The paper presents a technique for cost-effective and safe studying of conventional and critical flight regimes and control validation using an autonomous scaled aircraft model mounted in a three-degree-offreedom gimbal in a wind tunnel. The similarity of the dynamics at high angles of attack of the wind-tunnel model and the free-flying model is demonstrated. To suppress the wing rock and to prevent the stall, two control laws are designed using linear matrix inequalities and model reference adaptive control techniques. The controllers are tested in a semifree flight of the autonomous scaled model in the wind tunnel. Wing rock suppression and stall and spin prevention are demonstrated.C nΔδ e = ∂C n ∂Δδ e C nδ a = ∂C n ∂δ a C l ; C m ; C n = roll, pitch, and yaw moment coefficients C l0 ; C m0 ; C n0 = static values of roll, pitch, and yaw moment coefficients C mq = ∂C m ∂q c∕2V c = mean aerodynamic chord g = acceleration due to gravity I = matrix of moment of inertia I xx = moment of inertia in roll Iyy = moment of inertia in pitch I zz = moment of inertia in yaw k 1;2θ ; k 1;2ϕ ; k 1;2ψ = friction coefficients M a ; M g ; M f = aerodynamic, gravity, and gimbal friction moments p, q, r = roll, pitch, and yaw rates Q fθ ; Q fϕ ; Q fψ = components of friction moment S = reference wing area V = velocity α, β = angles of attack and sideslip δ = vector of control effectors ΔC lδ r ; ΔC nδ r = increment of roll and yaw moment coefficients due to rudder deflection Δx c:g: ; Δz c:g:= misalignment of the center of mass with respect to the center of gimbals δ e ; Δδ e ; δ a ; δ r = mean stabilator, differential stabilator, aileron, and rudder deflections ϕ; θ; ψ = rotational angles in gimbals in roll, pitch, and yaw