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This paper examines the geometry of a group of closed-loop manipulators with structures based on a planar, revolute jointed, five-bar chain. Of primary interest is the influence of the link lengths on the reachable workspace of the manipula tor. Unlike the commonly used open-loop manipulators, the entire workspace for a closed-loop manipulator will not be freely reachable, in general. The issues pertaining to the independent mobility of the driving links are discussed at length. A classification is made based on mobility criteria, and these mechanisms are further categorized into two types depending upon the influence of the link lengths on the ma nipulator's workspace. Based on this analysis, some general guidelines are laid down to assist the designer in making rational choices in selecting manipulator link lengths.

The present communication presents the new experimental CO 2 solubility data in an aqueous mixture of diethanolamine (DEA) and (2-aminoethyl)ethanolamine (AEEA) at CO 2 concentrations in the inlet gas stream from (10.13 to 20.27) kPa and temperatures from (303.14 to 333.14) K. The aqueous (DEA + AEEA) mixtures of total concentrations were chosen from (0.92 to 3.22) mol·kg −1 , and the mole fraction of AEEA in total amine was varied from 0.02 to 0.20. The findings point that the CO 2 solubility in a fixed total concentration of amine mixture becomes more at a higher AEEA mole fraction in total amine with a constant temperature and CO 2 concentration in the inlet gas stream. The CO 2 solubility in the amine mixture falls with the rise in temperature but rises with an increase in CO 2 concentration in the inlet gas stream. The highest amount of CO 2 solubility in (DEA + AEEA) mixtures was observed as 0.74 mol CO 2 /mol absorbent with AEEA mole fraction in total amine of 0.2 at a 1.84 mol·kg −1 total concentration of amine mixture and 313.14 K. The result of this work is compared with some of the most studied amine mixtures available in the literature. ■ INTRODUCTIONUninterrupted human activities have resulted in a significant increase of greenhouse gas concentrations in the environment over the past 200 years. By the year 2100, the average worldwide temperature may increase by (1.4 to 5.8)°C due to this increased amount of greenhouse gases as predicted by the various estimations of climate models. 1 The excessive release of greenhouse gases has caused the serious environmental problems like global warming found in nature. CO 2 , amounting an almost more than 50 % major share in greenhouse gases, produces more than 60 % of the increased greenhouse effect at present. CO 2 emissions mostly come from fossil-fuel based industries, 2 such as coal-fired thermal power generation, petroleum and natural gas based energy industries, and various metallurgical processes, responsible for sustainable economic growth. India is the fifth largest CO 2 contributor with approximately 5 % of the worldwide CO 2 emissions, and the increasing emission trend is likely to be continued. The energy scenario of WEO 2009 forecasts that CO 2 emissions in India will be more than 2.5 times that of the 2008 emission level by the year 2030 due to its economic growth. 3 The majority of these emissions is attributed to heat and electricity generation, which showed an enhanced CO 2 emission from 42 % in 1990 to 56 % in 2008. The transport sector contributes the smallest share of about 9 % of CO 2 emissions in 2008 among other sectors. These growing trends of CO 2 emissions raise the issue of low energy use and the need to invent efficient technologies for CO 2 capture from contaminated gas streams released from industrial origins. Chemical absorption is a mature technology and mostly used in postcombustion thermal power plants where the CO 2 concentration is very low (≤ 20 % by volume). This technology still has some limitations such as absorbent degrad...

Planetary monocular simultaneous localization and mapping (PM-SLAM), a modular, monocular SLAM system for use in planetary exploration, is presented. The approach incorporates a biologically inspired visual saliency model (i.e., semantic feature detection) for visual perception in order to improve robustness in the challenging operating environment of planetary exploration. A novel method of generating hybrid-salient features, using point-based descriptors to track the products of the visual saliency models, is introduced. The tracked features are used for rover and map state-estimation using a SLAM filter, resulting in a system suitable for use in long-distance autonomous (micro)rover navigation, and the inherent hardware constraints of planetary rovers. Monocular images are used as an input to the system, as a major motivation is to reduce system complexity and optimize for microrover platforms. This paper sets out the various components of the modular SLAM system and then assesses their comparative performance using simulated data from the Planetary and Asteroid Natural Scene Generation Utility (PANGU), as well as real-world datasets from the West Wittering field trials (performed by the STAR Lab) and the SEEKER field trials in Chile (performed by the European Space Agency). The system as a whole was shown to perform reliably, with the best performance observed using a combination of Hou-saliency and speeded-up robust features (SURF) descriptors with an extended Kalman filter, which performed with higher accuracy than a state-of-the-art, independently optimized visual odometry localization system on a challenging real-world dataset