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This paper examines the challenges associated with the efficient planning and operation of an E-grocery delivery system using Autonomous Delivery Robots (ADR) during unforeseen events. The primary objective is to minimize unfulfilled customer demands rather than focusing solely on cost reduction, considering the humanitarian aspect. To address this, a two-echelon vehicle routing problem is formulated, taking into account stochastic service times and demands. Two models, namely a deterministic model and a chance-constraint model, are employed to solve this problem. The results demonstrate that the chance-constraint model significantly reduces unmet demands compared to the deterministic model, particularly when the delivery deadline has a broad time window and the ADR/van speed ratio is moderate.