One of the most challenging issues for a selfsustaining robotic system is how to use its limited resources to accomplish a large variety of tasks. The scope of such tasks could include transportation, exploration, construction, inspection, maintenance, in-situ resource utilization, and support for astronauts. This paper proposes a modular and reconfigurable solution for this challenge by allowing a robot to support multiple modes of locomotion and select the appropriate mode for the task at hand. This solution relies on robots that are made of reconfigurable modules. Each locomotion mode consists of a set of characteristics for the environment type, speed, turning-ability, energy-efficiency, and recoverability from failures. This paper demonstrates a solution using the SuperBot robot that combines advantages from M-TRAN, CONRO, ATRON, and other chain-based and lattice-based robots. At the present, a single real SuperBot module can move, turn, sidewind, maneuver, and travel on batteries up to 500 m on carpet in an office environment. In physics-based simulation, SuperBot modules can perform multimodal locomotions such as snake, caterpillar, insect, spider, rolling track, H-walker, etc. It can move at speeds of up to 1.0 m/s on flat terrain using less than 6 W per module, and climb slopes of no less 40 degrees.

The influence of titanium diboride (TiB 2 ) loading on the dry sliding wear characteristics of aluminum 6063 matrix alloy-titanium diboride (Al/TiB 2 ) composite materials has been assessed using a pin-on disc wear tester at different loads. The composites with 5 and 10 wt% of fine TiB 2 particles were fabricated using stir casting technique. For comparison, as-cast of the base alloy were made under the same processing applied for Al/TiB 2 composites. The hardness of the composite materials was measured using Brinell hardness tester. Scanning electron microscopy (SEM) was used to analyze the wear surfaces of samples. The results indicate that fine TiB 2 particles markedly improved the wear performance of the aluminum 6063 matrix alloy. The coefficient of friction decreases with increase in the amount of TiB 2 , but this effect was more pronounced in dry sliding. Hardness of composites increased with increasing TiB 2 loading. The wear rates increase with increase in load and dependent upon TiB 2 loading in the base alloy. Among the composites tested, Al/TiB 2 composites containing 10 wt% TiB 2 exhibited superior wear resistance over the base alloy and 5 wt% Al/TiB 2 composites. These observations were correlated in terms of the TiB 2 loading in base alloy which resulted in the variations of the hardness.

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Computer vision is a significant component of human-computer interaction (HCI) processes in interactive control systems. In general, the interaction between humans and computers relies on the flexibility of the interactive visualization system. Electromyography (EMG) is a bioelectric signal used in HCI that can be captured noninvasively by placing electrodes on the human hand. Due to the impact of complex background, accurate recognition and analysis of human motion in real-time multitarget scenarios are considered challenging in HCI. Further, EMG signals of human hand motions are exceedingly nonlinear, and it is important to utilize a dynamic approach to address the noise problem in EMG signals. Hence, in this paper, the Optimized Noninvasive Human-Computer Interaction (ONIHCI) model has been proposed to predict human motion recognition. Average Intrinsic Mode Function (AIMF) has been used to reduce the noise factor in EMG signals. Furthermore, this paper introduces spatial thermographic imaging to overcome the conventional sensor problem, such as gesture recognition and human target identification in multitarget scenarios. The human motion behavior in spatial thermographic images is examined by target trajectory, and body movement kinematics is employed to classify human targets and objects. The experimental findings demonstrate that the proposed method reduces noise by 7.2% and improves accuracy by 97.2% in human motion recognition and human target identification.

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-This paper presents a modular and reconfigurable robot for multiple locomotion modes based on reconfigurable modules. Each mode consists of characteristics for the environment type, speed, turning-ability, energy-efficiency, and recoverability from failures. The paper demonstrates this solution by the Superbot robot that combines advantages from MTRAN, CONRO and others. Experimental results, both in real robots and in simulation, have shown the validity of the approach and demonstrated the movements of forward, backward, turn, sidewinder, maneuver, and travel on batteries up to 500 meters on a flat terrain. In physics-based simulation, Superbot can perform as snake, caterpillar, insect, spider, rolling track, Hwalker, etc., and move 1.0 meter/second on flat terrain with less than 6W/module, and climb slopes of no less 40 degrees.Index Terms -space robots, modular robots, selfreconfigurable and multifunctional robots.