Use of family member involvement for boosting family income

It is an obvious and much talked about fact that Sri Lanka has to concentrate in speeding up the resettlement process of persons who were affected by the war that was prevailing in the country over a period of 30 years. The families themselves have a key role to play in the process of reaching stability. This paper is constructed around the theme of "How the family members can support to boost the family income?' thus whilst welcoming efforts to initiate family businesses at a smaller scale, this paper also involves a discussion on how the family combinations of components of involvement contribute to the small family business success. The paper is based on the findings of a case study done on brassware industry small family businesses, which shows how some families have themselves become a key resource in the process of raising the economical stability in the family

Active SLAM using model predictive control and attractor based exploration

Active SLAM poses the challenge for an autonomous robot to plan efficient paths simultaneous to the SLAM process. The uncertainties of the robot, map and sensor measurements, and the dynamic and motion constraints need to be considered in the planning process. In this paper, the active SLAM problem is formulated as an optimal trajectory planning problem. A novel technique is introduced that utilises an attractor combined with local planning strategies such as Model Predictive Control (a.k.a. Receding Horizon) to solve this problem. An attractor provides high level task intentions and incorporates global information about the environment for the local planner, thereby eliminating the need for costly global planning with longer horizons. It is demonstrated that trajectory planning with an attractor results in improved performance over systems that have local planning alone. © 2006 IEEE

Active SLAM in structured environments

This paper considers the trajectory planning problem for line-feature based SLAM in structured indoor environments. The robot poses and line features are estimated using Smooth and Mapping (SAM) which is found to provide more consistent estimates than the Extended Kalman Filter (EKF). The objective of trajectory planning is to minimise the uncertainty of the estimates and to maximise coverage. Trajectory planning is performed using Model Predictive Control (MPC) with an attractor incorporating long term goals. This planning is demonstrated both in simulation and in a real-time experiment with a Pioneer2DX robot. ©2008 IEEE

Empowering communications challenged users using development kits

The rapid pace of technological advancement and its consequential widening digital divide has resulted in the marginalization of the disabled especially the communication challenged. The dearth of suitable technologies for the development of assistive technologies has served to further marginalize the communications challenged user population and widen this chasm even further. Given the varying levels of disability there and its associated requirement for customized solution based. This paper explains the use of a Software Development Kits (SDK) for the bridging of this communications divide through the use of industry poplar communications SDKs towards identification of requirements for communications challenged users as well as identification of appropriate frameworks for future development initiatives

A kyno-dynamic metric to plan stable paths over uneven terrain

A generic methodology to plan increasingly stable paths for mobile platforms travelling over uneven terrain is proposed in this paper. This is accomplished by extending the Fast Marching level-set method of propagating interfaces in 3D lattices with an analytical kyno-dynamic metric which embodies robot stability in the given terrain. This is particularly relevant for reconfigurable platforms which significantly modify their mass distribution through posture adaptation, such as robots equipped with manipulator arms or varying traction arrangements. Results obtained from applying the proposed strategy in a mobile rescue robot operating on simulated and real terrain data illustrate the validity of the proposed strategy. ©2010 IEEE

Planning under uncertainty using model predictive control for information gathering

This paper considers trajectory planning problems for autonomous robots in information gathering tasks. The objective of the planning is to maximize the information gathered within a finite time horizon. It is assumed that either the Extended Kalman Filter (EKF) or the Extended Information Filter (EIF) is applied to estimate the features of interest and the information gathered is expressed by the covariance matrix or information matrix. It is shown that the planning process can be formulated as an optimal control problem for a nonlinear control system with a gradually identified model. This naturally leads to the Model Predictive Control (MPC) planning strategy, which uses the updated knowledge about the model to solve a finite horizon optimal control problem at each time step and only executes the first control action. The proposed MPC framework is demonstrated through solutions to two challenging information gathering tasks: (1) Simultaneous planning, localization, and map building (SPLAM) and (2) Multi-robot Geolocation. It is shown that MPC can effectively deal with dynamic constraints, multiple robots/features and a range of objective functions. © 2006 Elsevier Ltd. All rights reserved

Trajectory planning for multiple robots in bearing-only target localisation

This paper provides a solution to the optimal trajectory planning problem in target localisation for multiple heterogeneous robots with bearing-only sensors. The objective here is to find robot trajectories that maximise the accuracy of the locations of the targets at a prescribed terminal time. The trajectory planning is formulated as an optimal control problem for a nonlinear system with a gradually identified model and then solved using nonlinear Model Predictive Control (MPC). The solution to the MPC optimisation problem is computed through Exhaustive Expansion Tree Search (EETS) plus Sequential Quadratic Programming (SQP). Simulations were conducted using the proposed methods. Results show that EETS alone performs considerably faster than EETS+SQP with only minor differences in information gain, and that a centralised approach outperforms a decentralised one in terms of information gain. We show that a centralised EETS provides a near optimal solution. We also demonstrate the significance of using a matrix to represent the information gathered. © 2005 IEEE

Plasmonic backscattering enhanced inverted photovoltaics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98669/1/ApplPhysLett_99_113306.pd

Photo-labile BODIPY protecting groups for glycan synthesis

Protective groups that can be selectively removed under mild conditions are an essential aspect of carbohydrate chemistry. Groups that can be selectively removed by visible light are particularly attractive because carbohydrates are transparent to visible light. Here, different BODIPY protecting groups were explored for their utility during glycan synthesis. A BODIPY group bearing a boron difluoride unit is stable during glycosylations but can be cleaved with green light as illustrated by the assembly of a trisaccharide