Rui Cortesão

Real-time adaptive control for haptic telemanipulation with Kalman active observers

This paper discusses robotic telemanipulation with Kalman active observers and online stiffness estimation. Operational space techniques, feedback linearization, discrete state space methods, augmented states, and stochastic design are used to control a robotic manipulator with a haptic device. Stiffness estimation only based on force data (measured, desired, and estimated forces) is proposed, avoiding explicit position information. Stability and robustness to stiffness errors are discussed, as well as real-time adaptation techniques. Telepresence is analyzed. Experiments show high performance in contact with soft and hard surfaces

On Kalman Active Observers

The paper introduces the Active Observer (AOB) algorithm in the framework of Kalman filters. The AOB reformulates the Kalman filter to accomplish model-reference adaptive control based on: (1) A desired closed loop system. (2) An extra equation to estimate an equivalent disturbance referred to the system input. An active state is introduced to compensate unmodeled terms, providing a feedforward compensation action. (3) Stochastic design of the Kalman matrices. Stability analysis with model errors is discussed. An example of robot force control with an external and unknown nonlinear disturbance is presented (SISO system). Another example of model-matching control for steer-by-wire (SBW) vehicles with underactuated structure is discussed (MIMO system).

Robust Control for Steer-by-Wire Vehicles

The design and analysis of steer-by-wire systems at the actuation and operational level is explored. At the actuation level, robust force feedback control using inverse disturbance observer structure and active observer algorithm is applied to enhance the robustness vs non-modelled dynamics and uncertain driver bio-impedance. At the operational level, the robustness aspects vs parameter uncertainties in vehicle dynamics and driver bio-impedance are issued and for a given target coupling dynamics between driver and vehicle the design task is converted to a model-matching problem. H∞ techniques and active observer algorithms are used to design the steer-by-wire controller. Robustness issues at both levels are covered by mapping stability bounds in the space of physical uncertain parameters.

Data fusion for robotic assembly tasks based on human skills

This work describes a data fusion architecture for robotic assembly tasks based on human sensory-motor skills. These skills are transferred to the robot through geometric and dynamic perception signals. Artificial neural networks are used in the learning process. The data fusion paradigm is addressed. It consists of two independent modules for optimal fusion and filtering. Kalman techniques linked to stochastic signal evolutions are used in the fusion algorithm. Compliant motion signals obtained from vision and pose sense are fused, enhancing the task performance. Simulations and peg-in-hole experiments are reported.

Real-time adaptive control for haptic manipulation with Active Observers

The paper discusses compliant motion control using Active Observers (AOBs) applied in robotic manipulators. Stochastic estimation strategies for haptic manipulation are introduced. Stability and robustness analysis is made as a function of stiffness mismatches. Real time adaptation is discussed.

Stability and transparency analysis of a haptic feedback controller for medical applications

This paper presents the performance analysis of a haptic feedback teleoperation system for robotic-assisted surgery. Through a haptic device, the surgeon tele-operates the medical instrument, fixed on a remote robot that may evolve in free space or in contact. In free space, the surgeon feels the motion of the robot. When contact with tissues occurs, an on-line environment stiffness estimation is performed using an extended Kalman filter with robot modeling error compensation and without considering the contact position. The quality of the telepresence will depend on this estimation. Based on the stability and transparency frequency analysis, the estimated parameter is used to tune the teleoperation scheme and to improve telepresence. The improvement is based on the stability of the haptic feedback teleoperation scheme new rearrangement in which we distinguish between voluntary and involuntary operator positions.

Haptic control for steer-by-wire systems

A force-feedback actuation loop for a steer-by-wire vehicle is developed. It is shown that the performance of this loop can be essentially improved by the introduction of a torque sensor. Model reference based control algorithms based on disturbance observer (DOB) and active observers (AOB) are applied to enhance the robustness vs. non-modelled dynamics and uncertain driver impedance.

Haptic Control Design for Robotic-Assisted Minimally Invasive Surgery

This paper discusses the design of a control system for robotic-assisted surgery with haptic feedback. The operational space control has a position-position teleopearation architecture with the phantom in the loop, enabling telepresence in free-space and contact. The null space control guarantees that surgical kinematic constraints are fulfilled. Both task and posture control run active observers (AOBs) in Cartesian domain, taking into account force, velocity and position signals. Experiments with a D2M2 (direct drive medical manipulator) robot are presented

Low cost wireless sensor network for in-field operation monitoring of induction motors

In most modern industries there is a growing need for high efficiency and availability in motor driver systems. Moreover, motor operation monitoring is necessary to the implementation of proper and cost-effective motor maintenance, repair and replacing strategies. In this paper, a wireless sensor network for in-field operation monitoring of three-phase squirrel-cage induction motors is proposed. The network is able to sink operation-related data of several motors to one central point. A number of hardware platforms for wireless sensor networks where evaluated and a low-cost platform was chosen to implement a simple operative communication protocol. The protocol is used to improve deployment and commissioning of the wireless network which are time and manpower consuming tasks and, therefore, has to be regarded as one of the main cost factors when using and implementing one such network. Furthermore in industrial environment node placement is not random because each node has to perform a specific task (e.g., monitoring a specific machine). All operational data is provided by a device that is able to read line currents, line-to-line voltages and temperatures, and performs several calculations such as power consumption, power factor, load factor, voltage and current unbalance. This device is also able to automatically manage the stator winding connection mode as a function of the linear current, in order to improve motor efficiency and power factor.

Explicit force control for manipulators with active observers

The article describes a systematic procedure to design a force controller with active observers (AOB). The design is based on pole placement using discrete state space theory. The concept of AOB is introduced as a starting point to perform robust estimates of the system state. The robustness of the system is accomplished through optimal noise processing embedded in the control strategy. The design was tested as a force controller in a Manutec R2 Robot at the DLR.