Achieving cooperation in a distributed multi-robot team

DMAPS (Distributed Multi-Agent Planning System) is a planning system developed for distributed multi-robot teams based on MAPS(Multi-Agent Planning System). MAPS assumes that each agent has the same global view of the environment in order to determine the most suitable actions. This assumption fails when perception is local to the agents: each agent has only a partial and unique view of the environment. DMAPS addresses this problem by creating a probabilistic global view on each agent by fusing the perceptual information from each robot. The experimental results on consuming tasks show that while the probabilistic global view is not identical on each robot, the shared view is still effective in increasing performance of the team.

Controlled trial of multidisciplinary care teams for acutely ill medical inpatients: enhanced multidisciplinary care

Background: Acute hospital general medicine services care for ageing complex patients, using the skills of a range of health-care providers. Evidence suggests that comprehensive early assessment and discharge planning may improve efficiency and outcomes of care in older medical patients. Aim: To enhance assessment, communication, care and discharge planning by restructuring consistent, patient-centred multidisciplinary teams in a general medicine service. Methods: Prospective controlled trial enrolling 1538 consecutive medical inpatients. Intervention units with additional allied health staff formed consistent multidisciplinary teams aligned with inpatient admitting units rather than wards; implemented improved communication processes for early information collection and sharing between disciplines; and specified shared explicit discharge goals. Control units continued traditional, referral-based multidisciplinary models with existing staffing levels. Results: Access to allied health services was significantly enhanced. There was a trend to reduced index length of stay in the intervention units (7.3 days vs 7.8 days in control units, P = 0.18), with no change in 6-month readmissions. in-hospital mortality was reduced from 6.4 to 3.9% (P = 0.03); less patients experienced functional decline in hospital (P = 0.04) and patients' ratings of health status improved (P = 0.02). Additional staffing costs were balanced by potential bed-day savings. Conclusion: This model of enhanced multidisciplinary inpatient care has provided sustainable efficiency gains for the hospital and improved patient outcomes.

Virtual teams and group member dissimilarity - Consequences for the development of trust

The consequences of demographic dissimilarity for group trust in work teams was examined in a virtual (computer-mediated) and a face-to-face (FTF) environment. Demographic dissimilarity (based on age, gender, country of birth, enrolled degree) was predicted to be negatively associated with group trust in the FTF environment but not in the computer-mediated environment. Participants worked in small groups on a creative task for 3 consecutive days. In the computer-mediated environment, participants worked on the task for an hour per day. In the FTF environment, participants worked on the task for 20 minutes per day. Partial support was found for the effectiveness of computer-mediated groups in reducing the negative consequences of dissimilarity. Age dissimilarity was negatively related to trust in FTF groups but not in computer-mediated groups. Birthplace dissimilarity was positively related to trust in computer-mediated groups. Implications for the successful management of virtual teams are discussed.

Exploring the impact of perceived LMX variability within work teams

According to Leader-Member Exchange (LMX) theory, leaders develop different quaUt}' reladonships with the employees they supervise. To date, Utde research has invesdgated the impact of such differendadon by the leader on workplace outcomes. The current research proposes a novel way to capture the extent of LMX variabiUt}' within a single work team, and subsequently investigates the impact of perceived LMX variability on workplace outcomes. Across multiple employed samples, participants reported poorer team relations (as indicated by low team cohesion and high conflict) when they perceived LMX variability to be high. Perceptions of poor team relations further impacted negatively upon individual affect variables. The findings suggest that leaders may need to exercise caution when developing different quality relationships amongst individuals within the same work team.

Transformational leadership within virtual teams: Examining the mediating influence of trust and role clarity for performance and knowledge sharing

Virtual teams differ from tradidonal, co-located teams in that they primarily communicate via informadon technolog}' such as email, video conferencing and web based coUaboradve environments rather than in a face-to-face medium. There has been a lack of empirical research into the influence that leadership has within virtual teams upon key outcomes such as performance and knowledge sharing. This paper examines antecedents of knowledge sharing and performance, namely role clarit)' and trust in a team leader. We predicted that transformadonal leadership would posidvely influence both performance and knowledge sharing within virtual teams. We also h^'pothesised that trust in a leader and role clarit)' would mediate both the associadon between transformadonal leadership and performance as well as the associadon between transformadonal leadership and knowledge sharing within virtual teams. Data was collected from a public sector organisadon using virtual teams, Pardcipants responded to a self-report quesdonnaire. Supervisor radngs of performance and knowledge sharing were also obtained. In general we found support for a posidve reladonship between transformadonal leadership and performance and knowledge sharing within virtual teams. Using mediated muldple regression, we found support for the mediadng role of trust in the leader and role clarit}' between transformadonal leadership and performance and knowledge sharing. Implicadons of the results are provided.

A global vision system for a robot soccer team

This paper describes the real time global vision system for the robot soccer team the RoboRoos. It has a highly optimised pipeline that includes thresholding, segmenting, colour normalising, object recognition and perspective and lens correction. It has a fast ‘paint’ colour calibration system that can calibrate in any face of the YUV or HSI cube. It also autonomously selects both an appropriate camera gain and colour gains robot regions across the field to achieve colour uniformity. Camera geometry calibration is performed automatically from selection of keypoints on the field. The system acheives a position accuracy of better than 15mm over a 4m × 5.5m field, and orientation accuracy to within 1°. It processes 614 × 480 pixels at 60Hz on a 2.0GHz Pentium 4 microprocessor.

Multi-robot control in highly dynamic, competitive environments

The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robot’s action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robot’s navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

Biologically inspired joint control for a humanoid robot

The GuRm is a 1.2m tall, 23 degree of freedom humanoid consuucted at the University of Queensland for research into humanoid robotics. The key challenge being addressed by the GuRw projcct is the development of appropriate learning strategies for control and coodinadon of the robot’s many joints. The development of learning strategies is Seen as a way to sidestep the inherent intricacy of modeling a multi-DOP biped robot. This paper outlines the approach taken to generate an appmpria*e control scheme for the joinis of the GuRoo. The paper demonsrrates the determination of local feedback control parameters using a genetic algorithm. The feedback loop is then augmented by a predictive modulator that learns a form of feed-fonward control to overcome the irregular loads experienced at each joint during the gait cycle. The predictive modulator is based on thc CMAC architecture. Results from tats on the GuRoo platform show that both systems provide improvements in stability and tracking of joint control.

A modified particle filter for simultaneous robot localization and landmark tracking in an indoor environment

This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.