Robotics and Intelligent Systems
Research in this area focuses on the development of new control methods for robot manipulators and mobile robots using intelligent control based on Neural Networks, Fuzzy Logics, Genetic Algorithms, etc. On going research includes Path planning and formation control of a group of collaborative mobile robots for search and rescue operations. New intelligent control methods are implemented on a group of five wireless mobile robots from DrRobotTMInc. Other on going research topics include vibration and shape control of smart structures, active suspension systems using magneto-rheological dampers, and the analysis and control of shape memory alloy (SMA) based robotic actuators (artificial muscles).
Single mobile robot from the robotics and control laboratory at the Department of Mechanical Engineering, Royal Military College of Canada
Three robots navigating around obstacles to arrive at three different target points
Development, Analysis and Synthesis of Cable-Based Robots
The use of cables as structural components (passive or actuated) in robots leads to significant reductions in the inertia of the robots' moving parts. As such, cable-based robots are strong candidates for applications requiring high-accelerations (e.g. pick and place robots) as well as those where robots of reduced mass are desirable (e.g. space robots). Research in this area is focused on the mechanics of cable-based robots with special attention being given to tensegrity robots, a relatively new type of robot where all structural components are subjected to either tensile or compressive forces (thus allowing for an extensive use of cables). Current research activities include: development of new robot architectures, workspace computation, stiffness analysis, dynamic modelling, and geometrical optimization using genetic algorithms. Working prototypes of robots are designed and built to support theoretical research.
Research in Control
The research interests include aspects of control systems: linear and nonlinear control, robust control and optimization using linear matrix inequality (LMI) framework. The applications focus particularly on control of electromechanical plants, robot arms and pneumatic actuators involving friction behaviour. These works are investigating the position tracking and the dynamic friction compensation techniques based on the LuGre and the generalized Maxwell-slip (GMS) models. Now, these researches are intending to develop new methods of nonlinear control for highly nonlinear dynamics based on the Kronecker product, power of matrices and vectors algebra and the LMI formalism.