Building a software architecture for a human-robot team using the ORCA framework

This paper considers the problem of building a software architecture for a human-robot team. The objective of the team is to build a multi-attribute map of the world by performing information fusion. A decentralized approach to information fusion is adopted to achieve the system properties of scalability and survivability. Decentralization imposes constraints on the design of the architecture and its implementation. We show how a Component-Based Software Engineering approach can address these constraints. The architecture is implemented using Orca – a component-based software framework for robotic systems. Experimental results from a deployed system comprised of an unmanned air vehicle, a ground vehicle, and two human operators are presented. A section on the lessons learned is included which may be applicable to other distributed systems with complex algorithms. We also compare Orca to the Player software framework in the context of distributed systems.

Adding a receding horizon to Locally Weighted Regression for learning robot control

There have been notable advances in learning to control complex robotic systems using methods such as Locally Weighted Regression (LWR). In this paper we explore some potential limits of LWR for robotic applications, particularly investigating its application to systems with a long horizon of temporal dependence. We define the horizon of temporal dependence as the delay from a control input to a desired change in output. LWR alone cannot be used in a temporally dependent system to find meaningful control values from only the current state variables and output, as the relationship between the input and the current state is under-constrained. By introducing a receding horizon of the future output states of the system, we show that sufficient constraint is applied to learn good solutions through LWR. The new method, Receding Horizon Locally Weighted Regression (RH-LWR), is demonstrated through one-shot learning on a real Series Elastic Actuator controlling a pendulum.

The role of cross-functional teams on the alignment between technology innovation effectiveness and operational effectiveness

Organisations are increasingly investing in complex technological innovations, such as enterprise information systems, with the aim of improving the operation of the business, and in this way gaining competitive advantage. However, the implementation of technological innovations tends to have an excessive focus on either technology innovation effectiveness, or the resulting operational effectiveness. Focusing on either one of them is detrimental to long-term performance. Cross-functional teams have been used by many organisations as a way of involving expertise from different functional areas in the implementation of technologies. The role of boundary spanning actors is discussed as they bring a common language to the cross-functional teams. Multiple regression analysis has been used to identify the structural relationships and provide an explanation for the influence of cross-functional teams, technology innovation effectiveness and operational effectiveness in the continuous improvement of operational performance. The findings indicate that cross functional teams have an indirect influence on continuous improvement of operational performance through the alignment between technology innovation effectiveness and operational effectiveness.

Functional heterogeneity as a two-dimensional concept : empirical evidence for new venture teams

Previous research on entrepreneurial teams has failed to settle the controversy over whether team heterogeneity helps or hinders new venture performance. Reconciling this inconsistency, this paper suggests a new conceptual approach to disentangle differential effects of team heterogeneity by modeling two separate heterogeneity dimensions, namely knowledge scope and knowledge disparity. Analyzing unique data on functional experiences of the members of 337 start-up teams, we find support for our contention of team heterogeneity as a two-dimensional concept. Results suggest that knowledge disparity negatively relates to both start-ups’ entrepreneurial and innovative performance. In contrast, we find knowledge scope to positively affect entrepreneurial performance, while it shows an inverse U-shaped relationship to innovative start-up performance.

Learning multidimensional joint control of a robot using receding horizon locally weighted regression

In this paper we explore the ability of a recent model-based learning technique Receding Horizon Locally Weighted Regression (RH-LWR) useful for learning temporally dependent systems. In particular this paper investigates the application of RH-LWR to learn control of Multiple-input Multiple-output robot systems. RH-LWR is demonstrated through learning joint velocity and position control of a three Degree of Freedom (DoF) rigid body robot.

It's only temporary: Time frame and the dynamics of creative project teams

The success of many knowledge-intensive industries depends on creative projects that lie at the heart of their logic of production. The temporality of such projects, however, is an issue that is insufficiently understood. To address this, we study the perceived time frame of teams that work on creative projects and its effects on project dynamics. An experiment with 267 managers assigned to creative project teams with varying time frames demonstrates that compared to creative project teams with a relatively longer time frame, project teams with a shorter time frame focus more on the immediate present, are less immersed in their task, and utilize a more heuristic mode of information processing. Furthermore, we find that time frame moderates the negative effect of team conflict on team cohesion. These results are consistent with our theory that the temporary nature of creative projects shapes different time frames among project participants, and that it is this time frame that is an important predictor of task and team processes.

The RatSLAM project : robot spatial navigation

Rats are superior to the most advanced robots when it comes to creating and exploiting spatial representations. A wild rat can have a foraging range of hundreds of meters, possibly kilometers, and yet the rodent can unerringly return to its home after each foraging mission, and return to profitable foraging locations at a later date (Davis, et al., 1948). The rat runs through undergrowth and pipes with few distal landmarks, along paths where the visual, textural, and olfactory appearance constantly change (Hardy and Taylor, 1980; Recht, 1988). Despite these challenges the rat builds, maintains, and exploits internal representations of large areas of the real world throughout its two to three year lifetime. While algorithms exist that allow robots to build maps, the questions of how to maintain those maps and how to handle change in appearance over time remain open. The robotic approach to map building has been dominated by algorithms that optimise the geometry of the map based on measurements of distances to features. In a robotic approach, measurements of distance to features are taken with range-measuring devices such as laser range finders or ultrasound sensors, and in some cases estimates of depth from visual information. The features are incorporated into the map based on previous readings of other features in view and estimates of self-motion. The algorithms explicitly model the uncertainty in measurements of range and the measurement of self-motion, and use probability theory to find optimal solutions for the geometric configuration of the map features (Dissanayake, et al., 2001; Thrun and Leonard, 2008). Some of the results from the application of these algorithms have been impressive, ranging from three-dimensional maps of large urban strucutures (Thrun and Montemerlo, 2006) to natural environments (Montemerlo, et al., 2003).

Gaussian process models for sensor-centric robot localisation

This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment

The two dimensions of virtual and collocated project teams or what project team members WANT and GET : an empirical study

The current paper compares and investigates the discrepancies in motivational drives of project team members with respect to their project environment in collocated and distributed (virtual) project teams. The set of factors, which in this context are called ‘Sense of Ownership’, is used as a scale to measure these discrepancies using one tailed t tests. These factors are abstracted from theories of motivation, team performance, and team effectiveness and are related to ‘Nature of Work’, ‘Rewards’, and ‘Communication’. It has been observed that ‘virtual ness’ does not seem to impact the motivational drives of the project team members or the way the project environments provide or support those motivational drives in collocated and distributed projects. At a more specific level in terms of the motivational drives of the project team (‘WANT’) and the ability of the project environment to provide or support those factors (‘GET’), in collocated project teams, significant discrepancies were observed with respect to financial and non financial rewards, learning opportunities, nature of work and project specific communication, while in distributed teams, significant discrepancies with respect to project centric communication, followed by financial rewards and nature of work. Further, distributed project environments seem to better support the team member motivation than collocated project environments. The study concludes that both the collocated and distributed project environments may not be adequately supporting the motivational drives of its project team members, which may be frustrating to them. However, members working in virtual team environments may be less frustrated than their collocated counterparts as virtual project environments are better aligned with the motivational drives of their team members vis-à-vis the collocated project environments.

The two dimensions of virtual and collocated project teams or what project team members WANT and GET : empirical evidence

The current paper compares and investigates the discrepancies in motivational drives of project team members with respect to their project environment in collocated and distributed (virtual) project teams. The set of factors, which in this context are called ‘Sense of Ownership’, is used as a scale to measure these discrepancies using one tailed t tests. These factors are abstracted from theories of motivation, team performance, and team effectiveness and are related to ‘Nature of Work’, ‘Rewards’, and ‘Communication’. It has been observed that ‘virtualness’ does not seem to impact the motivational drives of the project team members or the way the project environments provide or support those motivational drives in collocated and distributed projects. At a more specific level in terms of the motivational drives of the project team (‘WANT’) and the ability of the project environment to provide or support those factors (‘GET’), in collocated project teams, significant discrepancies were observed with respect to financial and non financial rewards, learning opportunities, nature of work and project specific communication, while in distributed teams, significant discrepancies with respect to project centric communication, followed by financial rewards and nature of work. Further, distributed project environments seem to better support the team member motivation than collocated project environments. The study concludes that both the collocated and distributed project environments may not be adequately supporting the motivational drives of its project team members, which may be frustrating to them. However, members working in virtual team environments may be less frustrated than their collocated counterparts as virtual project environments are better aligned with the motivational drives of their team members vis-à-vis the collocated project environments.

ACE research vignette 018 : experiments in the MBA classroom : the case of time frames in project teams

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepeneurship researchers. In this vignette, Dr Rene Bakker considers project team dynamics and how executive education can be enriched by studying them in the classroom.