In the context of control, the motion of a legged robot is very challenging compared with traditional fixed manipulator. Recently, many researches have been conducted to control the motion of legged robot with different techniques. On the other hand, manipulation tasks have been addressed in many applications. These researches solved either the mobility or the manipulation problems, but integrating both properties in one system is still not available. In this thesis, a control algorithm is presented to control both locomotion and manipulation in a six legged robot. Landmines detection process is considered as a case study of this project to accelerate the mine detection operation by performing both walking and scanning simultaneously. In order to qualify the robot to perform more tasks in addition to the walking task, the joint redundancy of the robot is exploited optimally. The tasks are arranged according to their importance to high level of priority and low level of priority. A new task priority redundancy resolution technique is developed to overcome the effect of the algorithmic singularities and the kinematic singularity. The computational aspects of the solution are also considered in view of a real-time implementation. Due to the dynamic changes in the size of the robot motion space, the algorithm has the ability to make a trade-off between the number of achieved tasks and the imposed constraints. Furthermore, an appropriate hierarchy is imposed in order to ensure an accurate decoupling between the executed tasks. The dynamic effect of the arm on the overall performance of the robot is attenuated by reducing the optimisation variables. The effectiveness of the method is evaluated on a Computer Aided Design (CAD) model and the simulations of the whole operation are conducted using MATLAB and SimMechanics.

The purpose of the current studies was to determine whether "matches", or fit, between actual task control and participants' desire for control over their environment lead to better stress and task performance outcomes than "mismatches", or misfit, in high work demand environments only. These studies also investigated the mediating effects of cognitive stressor appraisals and stress, as well as the moderating influence of hardiness on threat appraisals. Data were collected on 366 undergraduate students, who were asked to complete individual difference measures and engage in timed performance tasks. Results indicated no significant interactions between actual task control and desire for control for the outcomes of cognitive stressor appraisals, experienced stress, or task performance. No mediating influence was found for cognitive appraisals or stress, nor was there a buffering effect of hardiness on the cognitive appraisal process. Despite the non-significant results, the effects on task performance trended in the predicted direction in both studies, such that the highest task performance was found in cases of match between actual task control and desire for control, whereas the lowest task performance was found in cases of mismatch. These findings yield some support for Person-Environment Fit theory, demonstrating that actual task control and desire for control should be considered together when predicting task performance in workplace contexts.