A feasible study of EEG-driven assistive robotic system for stroke rehabilitation

Stroke is a medical emergency and can cause a neurological damage, affecting the motor and sensory systems. Harnessing brain plasticity should make it possible to reconstruct the closed loop between the brain and the body, i.e., association of the generation of the motor command with the somatic sensory feedback might enhance motor recovery. In order to aid reconstruction of this loop with a robotic device it is necessary to assist the paretic side of the body at the right moment to achieve simultaneity between motor command and feedback signal to somatic sensory area in brain. To this end, we propose an integrated EEG-driven assistive robotic system for stroke rehabilitation. Depending on the level of motor recovery, it is important to provide adequate stimulation for upper limb motion. Thus, we propose an assist arm incorporating a Magnetic Levitation Joint that can generate a compliant motion due to its levitation and mechanical redundancy. This paper reports on a feasibility study carried out to verify the validity of the robot sensing and on EEG measurements conducted with healthy volunteers while performing a spontaneous arm flexion/extension movement. A characteristic feature was found in the temporal evolution of EEG signal in the single motion prior to executed motion which can aid in coordinating timing of the robotic arm assistance onset.

Enriching enterprise resource planning systems for strategic advantage: a semiotic motivated approach

Enterprise Resource Planning is often endorsed as a means to facilitate strategic advantage for businesses. The scarcity of resources is the method by which some businesses maintain their position. However, the ubiquitous trend towards the adoption of Enterprise Resourcing Planning systems coupled with market saturation makes the promise of advantage less compelling. Reported in this paper is a proposed solution based upon semiotic theory that takes a typical Enterprise Resource Planning deployment scenario and shapes it according to the needs of people in post-implementation contexts to leverage strategic advantage in different ways.

Multi-vehicle planning using RRT-connect

The problem of planning multiple vehicles deals with the design of an effective algorithm that can cause multiple autonomous vehicles on the road to communicate and generate a collaborative optimal travel plan. Our modelling of the problem considers vehicles to vary greatly in terms of both size and speed, which makes it suboptimal to have a faster vehicle follow a slower vehicle or for vehicles to drive with predefined speed lanes. It is essential to have a fast planning algorithm whilst still being probabilistically complete. The Rapidly Exploring Random Trees (RRT) algorithm developed and reported on here uses a problem specific coordination axis, a local optimization algorithm, priority based coordination, and a module for deciding travel speeds. Vehicles are assumed to remain in their current relative position laterally on the road unless otherwise instructed. Experimental results presented here show regular driving behaviours, namely vehicle following, overtaking, and complex obstacle avoidance. The ability to showcase complex behaviours in the absence of speed lanes is characteristic of the solution developed.

Motion planning of autonomous vehicles in a non-autonomous vehicle environment without speed lanes

Planning is one of the key problems for autonomous vehicles operating in road scenarios. Present planning algorithms operate with the assumption that traffic is organised in predefined speed lanes, which makes it impossible to allow autonomous vehicles in countries with unorganised traffic. Unorganised traffic is though capable of higher traffic bandwidths when constituting vehicles vary in their speed capabilities and sizes. Diverse vehicles in an unorganised exhibit unique driving behaviours which are analysed in this paper by a simulation study. The aim of the work reported here is to create a planning algorithm for mixed traffic consisting of both autonomous and non-autonomous vehicles without any inter-vehicle communication. The awareness (e.g. vision) of every vehicle is restricted to nearby vehicles only and a straight infinite road is assumed for decision making regarding navigation in the presence of multiple vehicles. Exhibited behaviours include obstacle avoidance, overtaking, giving way for vehicles to overtake from behind, vehicle following, adjusting the lateral lane position and so on. A conflict of plans is a major issue which will almost certainly arise in the absence of inter-vehicle communication. Hence each vehicle needs to continuously track other vehicles and rectify plans whenever a collision seems likely. Further it is observed here that driver aggression plays a vital role in overall traffic dynamics, hence this has also been factored in accordingly. This work is hence a step forward towards achieving autonomous vehicles in unorganised traffic, while similar effort would be required for planning problems such as intersections, mergers, diversions and other modules like localisation.

Planning autonomous vehicles in the absence of speed lanes using lateral potentials

Chaotic traffic, prevalent in many countries, is marked by a large number of vehicles driving with different speeds without following any predefined speed lanes. Such traffic rules out using any planning algorithm for these vehicles which is based upon the maintenance of speed lanes and lane changes. The absence of speed lanes may imply more bandwidth and easier overtaking in cases where vehicles vary considerably in both their size and speed. Inspired by the performance of artificial potential fields in the planning of mobile robots, we propose here lateral potentials as measures to enable vehicles to decide about their lateral positions on the road. Each vehicle is subjected to a potential from obstacles and vehicles in front, road boundaries, obstacles and vehicles to the side and higher speed vehicles to the rear. All these potentials are lateral and only govern steering the vehicle. A speed control mechanism is also used for longitudinal control of vehicle. The proposed system is shown to perform well for obstacle avoidance, vehicle following and overtaking behaviors.

A good enough approach to setting planning obligations

In this paper we propose an alternative model of, what is often called, land value capture in the planning system. Based on development viability models, negotiations and policy formation regarding the level of planning obligations have taken place at the local level with little clear guidance on technique, approach and method. It is argued that current approaches are regressive and fail to reflect how the ability of sites to generate planning gain can vary over time and between sites. The alternative approach suggested here attempts to rationalise rather than replace the existing practice of development viability appraisal. It is based upon the assumption that schemes with similar development values should produce similar levels of return to the landowner, developer and other stakeholders in the development as well as similar levels of planning obligations in all parts of the country. Given the high level of input uncertainty in viability modelling, a simple viability model is ‘good enough’ to quantify the maximum level of planning obligations for a given level of development value. We have argued that such an approach can deliver a more durable, equitable, simpler, consistent and cheaper method for policy formation regarding planning obligations.

Area-wide development viability appraisals: the concept of threshold land value within a UK planning context

Area-wide development viability appraisals are undertaken to determine the economic feasibility of policy targets in relation to planning obligations. Essentially, development viability appraisals consist of a series of residual valuations of hypothetical development sites across a local authority area at a particular point in time. The valuations incorporate the estimated financial implications of the proposed level of planning obligations. To determine viability the output land values are benchmarked against threshold land value and therefore the basis on which this threshold is established and the level at which it is set is critical to development viability appraisal at the policy-setting (area-wide) level. Essentially it is an estimate of the value at which a landowner would be prepared to sell. If the estimated site values are higher than the threshold land value the policy target is considered viable. This paper investigates the effectiveness of existing methods of determining threshold land value. They will be tested against the relationship between development value and costs. Modelling reveals that threshold land value that is not related to shifts in development value renders marginal sites unviable and fails to collect proportionate planning obligations from high value/low cost sites. Testing the model against national average house prices and build costs reveals the high degree of volatility in residual land values over time and underlines the importance of making threshold land value relative to the main driver of this volatility, namely development value.

Addressing uncertainty in adaptation planning for agriculture

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop–climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.

Economic transformation in Ghana: where will the path lead?

In the context of the Ghanaian government’s objective of structural transformation with an emphasis on manufacturing, this paper provides a case study of economic transformation in Ghana, exploring patterns of growth, sectoral transformation, and agglomeration. We document and examine why, despite impressive growth and poverty reduction figures, Ghana’s economy has exhibited less transformation than might be expected for a country that has recently achieved middle-income status. Ghana’s reduced share of agriculture in the economy, unlike many successfully transformed countries in Asia and Latin America, has been filled by services, while manufacturing has stagnated and even declined. Likely causes include weak transformation of the agricultural sector and therefore little development of agroprocessing, the emergence of consumption cities and consumption-driven growth, upward pressure on the exchange rate, weak production linkages, and a poor environment for private-sector-led manufacturing.

Fractal spaces in planning and governance

This paper discusses concepts of space within the planning literature, the issues they give rise to and the gaps they reveal. It then introduces the notion of 'fractals' borrowed from complexity theory and illustrates how it unconsciously appears in planning practice. It then moves on to abstract the core dynamics through which fractals can be consciously applied and illustrates their working through a reinterpretation of the People's Planning Campaign of Kerala, India. Finally it highlights the key contribution of the fractal concept and the advantages that this conceptualisation brings to planning.