Path planning for wheeled mobile robots on partially known uneven terrain is an open challenge since robot motions can be strongly influenced by terrain with incomplete environmental information such as locally detected obstacles and impassable terrain areas. This paper proposes a hierarchical path planning approach for a wheeled robot to move in a partially known uneven terrain. We first model the partially known uneven terrain environment respecting the terrain features, including the slope, step, and unevenness. Second, facilitated by the terrain model, we use A${}^{\star }$ algorithm to plan a global path for the robot based on the partially known map. Finally, the Q-learning method is employed for local path planning to avoid locally detected obstacles in close range as well as impassable terrain areas when the robot tracks the global path. The simulation and experimental results show that the designed path planning approach provides satisfying paths that avoid locally detected obstacles and impassable areas in a partially known uneven terrain compared with the classical A${}^{\star }$ algorithm and the artificial potential field method.

This paper investigates the task assignment problem for one truck and one drone to deliver packages to a group of customer locations. The truck, carrying a large number of packages, can only travel between a group of prescribed street-stopping/parking locations to replenish the drone with both packages and batteries. The drone can carry multiple packages simultaneously to serve customers sequentially within its limited operation range. The objective is to reduce the amount of time it takes the drone to deliver the necessary package to the last customer while taking into account its operation range and loading capacity. First, the package delivery task assignment problem is shown to be an NP-hard problem, which guides us to design heuristic task assignment algorithms. Secondly, based on graph theory, a lower bound on the minimum time for the drone to serve the last customer is achieved to approximately evaluate the performance of a task assignment algorithm. Third, several decoupled heuristic algorithms are designed to sequentially plan the routes for the drone and the truck. Two coupled heuristic algorithms, namely the improved nearest inserting algorithm and the improved minimum marginal-cost algorithm, are proposed to simultaneously plan the routes for the drone and the truck. Numerical simulations demonstrate that the improved minimum marginal-cost algorithm reduces the total service time by 14.93% and 14.06% on average compared with the existing decoupled two-phase algorithm TPA and the coupled greedy algorithm, respectively. In the best case, it reduces the total service time by 41.71% and 40.11% compared with the TPA and the coupled greedy algorithm, respectively.

Although differentiated thyroid carcinoma (DTC) has a good prognosis and survival rate, long-term medication and recurrence monitoring might be needed. The factors that affect postoperative health-related quality of life (HRQoL) in patients with DTC in different regions remain unclear or conflicting. The purpose of this study was to assess the factors that influence the HRQoL of DTC patients after surgery. This study selected 174 patients with DTC who underwent thyroidectomy. Additionally, 174 participants who were matched by age, gender, and socioeconomic status were recruited from the population as the control group. Both the DTC and control population groups were invited to answer the HRQoL questionnaire SF-36. Scores on seven domains of the HRQoL including role-physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role-emotional (RE), and mental health (MH), were significantly lower for DTC patients than for the control population. The patients with no comorbidities had much higher scores on the 8 domains of the SF-36 than DTC patients with two or more comorbidities (all P < 0.05). Hypertension, diabetes and depression were the predictive factors of a poor Physical Component Summary (PCS) score and diabetes and depression were predictive factors of the Mental Component Summary (MCS) score at one year of follow-up (all P < 0.05). HRQoL is significantly influenced by many sociodemographic and clinical factors. Hypertension, diabetes and depression had a negative impact on HRQoL in DTC patients. More attention and targeted intervention should be given to DTC patients after surgery to improve quality of life.