Hybrid Robotic Control  The technology being developed addresses the problem that most commercial robotic systems use only joint level control and not task level. The innovation involves adding task level to join level control that results in the robotic arm being more accurate. By adding task level control there are also a host of new application areas related to sensors and the resultant information management for a distributed system of robotic modules. |
Control System Design and Nonlinear Models An emerging area of research is the utilization of interspacecraft Coulomb forces for both position and attitude control. This has applications from spacecraft formation flying to active “virtual” structures that are highly reconfigurable and robust to individual spacecraft failure. Spacecraft force coupling and the nonlinear electrostatic force behavior provide a variety of interesting technical challenges from nonlinear control to optimal formation design. Similar research topic areas such as, nonlinear control, system simulation, nonlinear system parameter identification and optimization, are present in most of his ongoing projects. Examples include active control of diesel engine aftertreatment systems, at-sea ship crane control, and hydraulic system parameter identification. Another research area is focused on increasing robot-based, flexible material throughput for manufacturing
applications. The system dynamics of the part are exploited, in conjunction with vision-based trajectory optimization, to minimize maneuver time. |
Robotic Control and Nonlinear Systems Analysis  This research program has yielded outcomes in a number of interrelated domains including development of robot kinematic, dynamic formulations and control systems by geometric and topologic methods; a new robotic model for simplification of robotic control algorithms and its real-time realization;an optimal design criterion for robotic manipulators; a redundant robot arm with seven joints and designed its controller, hardware, interface and software with applications to automation.
Related research has resulted in development of two classes of intelligent control strategies. The first is based on linguistics and automata technique with translation schemata, and rule-based systems The second is based on the applications of learning control, supervisory control schemes, neural networks, fuzzy logic and hierarchical intelligent control systems.
Finally, this research program has focused on properties and characteristics of nonlinear systems, stability and stabilization, differential geometry methods for nonlinear control systems analysis and applications. |
Memory Controller Interconnect and Policy Determination This research program is focused on developing novel interconnect techniques and DRAM controller management policies to reduce the latency to memory access. The research examines the potential for improved performance when the memory controller changes from a static control policy to a dynamic control scheme. For example, as the amount of state present in DRAM devices increases, the available set of memory controller policy decisions also increases; this increased flexibility allows an intelligent memory controller to optimize controller policies to achieve increased performance. This impact is simulated over a variety of interconnection topologies from the current NorthBridge to a CMP architecture with multiple DRAM busses. |
Robotics and Embedded Systems Laboratory The robotics and embedded systems laboratory conducts research on large scale networked system of distributed robotics and sensors, body sensor networks and sensor network applications in intelligent transportation systems. Current lines of inquiry include scalable coordination for hybrid sensor/actuator networks, multi-robot and sensor coordination, body sensor networks, sensor network localization using mobile robots, mobile sensor navigation in hybrid sensor networks, and real-time protocols for sensor networks. |
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