Based on its simple structure, base-fixed actuators, high payload capacity, high accuracy, and high mechanical rigidity, the 3-RlowbarRR mechanism is a valuable planar parallel manipulator. However, the 3-RlowbarRR mechanism is known to have singular loci within its workspace affecting its use. In this paper, singularity avoidance of the 3-RlowbarRR mechanism using kinematic redundancy is presented. First, singularity analysis of the proposed 3-RlowbarPlowbarRR mechanism is described and a simple and effective redundancy resolution algorithm based on local optimization suitable for real-time control is developed. Here, the cost function in the optimization is designed to avoid the most problematic singularity configurations, where the end-effector can be locally moved even though all actuated joints are locked. Results from simulation show that the resultant 3-RlowbarPlowbarRR mechanism can be used to avoid singularities associated with the 3-RlowbarRR mechanism, and enlarges the usable workspace.

In this paper, a collision detection and identification method of a manipulator, using base and wrist force/torque sensors, is presented. An impact model is used to simulate the interaction between the manipulator and the human or environment. A neural network approach and a model based method are developed to detect the collision forces and disturbance torques on the joints of the manipulator. The experimental results illustrate the validity of the developed collision detection and identification scheme.

One approach towards improving the reliability of high-performance robotic systems is to allow for the automatic reconfiguration of the robot's control system to accommodate actuator failure and/or damage. The new concept of the extended plant and its identification in closed loop is introduced for developing a reconfigurable robot manipulator controller. It is made possible through the use of artificial neural networks. A simulation study demonstrates the effectiveness of the developed control algorithm.

This paper examines dynamic modeling of differentially and conventionally steered wheeled mobile robots (WMRs) for high load applications such as highway maintenance and construction. Dynamic models including an accurate tire representation are developed for both types of WMRs. In addition to these dynamic models, both kinematic and simplified dynamic models are also developed for purposes of comparison. The simplified dynamic model utilizes a greatly simplified tire representation. Through the use of simulation, the limits of validity of each of the models is determined thus allowing for the selection of the model most appropriate for a given application. Additionally, the accuracy of the dead reckoning vehicle tracking process is investigated.>