This work investigate temporal planning to synthesize personalized physical rehabilitation programs. The first contribution of the work concerns the representation of (heterogeneous) clinical and spatial constraints into a planning framework. The second contribution is the integration of numerical and symbolic reasoning to synthesize technically valid and coherent plans with respect to different clinical objectives. The experimental section discusses the developed planner from a technical view, assessing solving and personalization capabilities, and from a clinical view, assessing the efficacy of plans on the involved patients.

Industry 4.0 is pushing forward the need for symbiotic interactions between physical and virtual entities of production environments to realize increasingly flexible and customizable production processes. This holds especially for human–robot collaboration in manufacturing, which needs continuous interaction between humans and robots. The coexistence of human and autonomous robotic agents raises several methodological and technological challenges for the design of effective, safe, and reliable control paradigms. This work proposes the integration of novel technologies from Artificial Intelligence, Control and Augmented Reality to enhance the flexibility and adaptability of collaborative systems. We present the basis to advance the classical human-aware control paradigm in favor of a user-aware control paradigm and thus personalize and adapt the synthesis and execution of collaborative processes following a user-centric approach. We leverage a manufacturing case study to show a possible deployment of the proposed framework in a real-world industrial scenario.

Timeline-based Planning and Scheduling (P&S) usually deals with two main sources of uncertainty: some components may depend on an external environment and cannot be planned; there may be tasks whose duration cannot be exactly foreseen in advance. Such uncertainties are formally defined and consequent controllability issues have been addressed, focusing on dynamic controllability. In this work, we present a new software prototype, tiga2exec, for dynamic controllable execution of timeline-based plans leveraging recent results gathered from the integration of P&S and Model Checking techniques. tiga2exec is deployed in a timeline-based planning system to control plan execution guaranteeing dynamic controllability. A preliminary experimental evaluation is also presented.