In this study, empirical results of a market-based task allocation method for heterogeneous robot teams and different type of tasks are presented. Proposed method assigns tasks to robots through a parallel multi-item auction-based process. The main contribution of the proposed method is energy-based bid calculations which take into account both the heterogeneity of the robot team and features of the tasks. Multi-robot task allocation problem is considered as the optimal assignment problem and the Hungarian algorithm is used to clear the auctions. Simulations are carried out using energy-, distance- and time-based bid calculation methods. Effectiveness of the proposed energy-based bid calculation method is shown by comparing the results of these three methods. The methods are implemented using a three-type task set: cleaning a space, carrying an object and monitoring. The tasks may have different sensitivity and/or priority levels. Simulations show that the energy-based bid calculation method completes greater number of high-sensitivity tasks compared to other two methods while consuming almost the same amount of energy. Additionally, the energy-based method has a filtering behaviour for high-priority tasks.