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This paper proposes a new tri-objective scheduling algorithm called Heterogeneous Reliability-Driven Energy-Efficient Duplication-based (HRDEED) algorithm for heterogeneous multiprocessors. The goal of the algorithm is to minimize the makespan (schedule length) and energy consumption, while maximizing the reliability of the generated schedule. Duplication has been employed in order to minimize the makespan. There is a strong interest among researchers to obtain high-performance schedules that consume less energy. To address this issue, the proposed algorithm incorporates energy consumption as an objective. Moreover, in order to deal with processor and link failures, a system reliability model is proposed. The three objectives, i.e., minimizing the makespan and energy, while maximizing the reliability, have been met by employing a method called Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). TOPSIS is a popular Multi-Criteria Decision-Making (MCDM) technique that has been employed to rank the generated Pareto optimal schedules. Simulation results demonstrate the capability of the proposed algorithm in generating short, energy-efficient and reliable schedules. Based on simulation results, we observe that HRDEED algorithm demonstrates an improvement in both the energy consumption and reliability, with a reduced makespan. Specifically, it has been shown that the energy consumption can be reduced by 5–47%, and reliability can be improved by 1–5% with a 1–3% increase in makespan.

There are many interests in developing life-like robots, or robots which are both intelligent and autonomous. And, one obvious characteristics of life-like creatures is that they can autonomously develop and learn during their life span. Such abilities obviously depend on the ways of designing human-like minds. Then, a fundamental question is how to devise the innate, or built-in, principles behind the blueprint of a human-like mind, and to apply these findings to guide the design of the mind of life-like robots. In the literature, there are two schools of thoughts. One advocates the study of the nervous systems of biological brains (e.g. human brain) until the discovery of the blueprint of a mind. The second approach is to follow the path of invention and validation until the full understanding of physical principles which enable the design of an artificial mind that is as good as a biological mind. This paper embraces the second approach, and aims at formulating a new ground which could guide the design of the minds of life-like robots at various stages. In particular, the discussion is focused on answering the question of what life is from an engineering point of view. And, we approach the answer by examining the key steps of evolution from non-life to life. In this paper, five key steps of evolution from non-life to life will be discussed in detail. They are embodiment of energy flow, embodiment of signal flow, embodiment of knowledge flow, embodiment of decision flow, and embodiment of awareness flow. These findings are grounded on our engineering works toward the development of low-cost humanoid (LOCH) robot, and offer a unique perspective and an engineering basis. Whenever possible, the discussions in this paper are supported by real results of experiments on real robots.

This paper proposes an energy control method for dynamic obstacle crossing by a planar biped. This approach was tested in a simulation where it was found to enable the biped robot to cross obstacles of different heights, due to inertial forces, by leaning with the front foot on the obstacles. The propulsion energy of the system is produced by the rear leg, which is endowed with four actuated degrees-of-freedom (hip, knee, ankle, toes), and is controlled by force control with four degrees-of-freedom in the non-singular case, and three degrees-of-freedom in the singular case. This paper identifies ten geometric, energetic and servo-control parameters necessary for dynamic obstacle crossing. The methodology presented allowed the dynamic crossing of an obstacle up to 20 cm high, at which point the joint torque limit for the propelling ankle was reached.