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.

Modern methods for traditional tasks: Developing an electronic version of student fieldwork assessment at The University of Queensland.

Fieldwork placements are an integral part of many professional tertiary programmes. At The University of Queensland, Occupational Therapy students undertake block fieldwork affiliations off campus at a wide range of sites as part of their studies. Students’ fieldwork performance has traditionally been assessed using a hard copy format of the Student Placement Evaluation Form (SPEF), which is posted to the university on completion by the clinical supervisor. This project aimed to develop an electronic version of the UQ Occupational Therapy Student Placement Evaluation Form (SPEF), to allow the assessment to be completed and returned in an on line format. Practitioners had become very comfortable with using the existing print based form so in order to encourage and assist users to extend beyond their comfort zones, numerous steps were taken to ease the learning process including incorporating the existing page layout, consistent colour coding, considerable user instruction, testing and software enhancement cycles. Additionally, the e-version of the SPEF aimed to provide a range of benefits such as on screen assistance in the form of instructions, roll overs and feedback to supervisors, increased accuracy, faster completion, cost savings to the School, up to date design, improved security and confidential and anonymous storage of fieldwork results for potential future research.