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Habitats Directive (92/43/EEC) is the cornerstone of nature conservation in Europe and is at the core of the EU Biodiversity Strategy for 2030. There is room, however, for its improvement, at least for northern Italy, where ambiguities in the definition of habitat types of Annex I of the Habitats Directive are not novel and interpretation difficulties have been highlighted. Sharpening the characterization of habitat types represents an opportunity for lowering classification uncertainties and improving conservation success. With the aim to refine the definitions of habitat types and associated typical species of the Habitats Directive, a group of vegetation scientists of the Italian Society of Vegetation Science based in northern Italy made the exercise of finding viable proposals for those habitat types having a problematic interpretation in the Alpine biogeographical region of Italy. Such proposals arise from group discussions among scientists, and professionals, thus offering a shared view. We prepared 9 habitat proposals important for this geographic area. They include new habitat types at the European level, new subtypes within pre-existing habitat types, including some adjustments of the recently proposed subtypes with respect to northern Italy, and recognition of priority criteria for a pre-existing habitat type. With a vision of tailored conservation, our proposals represent a starting point in view of a future update of Annex I. Furthermore, the list of typical species could be useful for preparing expert systems for automatic classification. Irrespective of legally binding solutions in place, we caution these proposals represent relevant baseline conservation indications that local and regional administrations of the Alpine Arch should consider.

We present a real time algorithm for humanoid 3D walking and/or running based on a Model Predictive Control (MPC) approach. The objective is to generate a stable gait that replicates a footstep plan as closely as possible, that is, a sequence of candidate footstep positions and orientations with associated timings. For each footstep, the plan also specifies an associated reference height for the Center of Mass (CoM) and whether the robot should reach the footstep by walking or running. The scheme makes use of the Variable-Height Inverted Pendulum (VH-IP) as a prediction model, generating in real time both a CoM trajectory and adapted footsteps. The VH-IP model relates the position of the CoM to that of the Zero Moment Point (ZMP); to avoid falling, the ZMP must be inside a properly defined support region (a 3D extension of the 2D support polygon) whenever the robot is in contact with the ground. The nonlinearity of the VH-IP is handled by splitting the gait generation into two consecutive stages, both requiring to solve a quadratic program. Thanks to a particular triangular structure of the VH-IP dynamics, the first stage deals with the vertical dynamics using the Ground Reaction Force (GRF) as a decision variable. Using the prediction given by the first stage, the horizontal dynamics become linear time-varying. During the flight phases, the VH-IP collapses to a free-falling mass model. The proposed formulation incorporates constraints in order to maintain physically meaningful values of the GRF, keep the ZMP in the support region during contact phases, and ensure that the adapted footsteps are kinematically realizable. Most importantly, a stability constraint is enforced on the time-varying horizontal dynamics to guarantee a bounded evolution of the CoM with respect to the ZMP. Furthermore, we show how to extend the technique in order to perform running on tilted surfaces. We also describe a simple technique that receives input high-level velocity commands and generates a footstep plan in the form required by the proposed MPC scheme. The algorithm is validated via dynamic simulations on the full-scale humanoid robot HRP-4, as well as experiments on the small-sized robot OP3.