61 research outputs found
A model-based residual approach for human-robot collaboration during manual polishing operations
A fully robotized polishing of metallic surfaces may be insufficient in case of parts with complex geometric shapes, where a manual intervention is still preferable. Within the EU SYMPLEXITY project, we are considering tasks where manual polishing operations are performed in strict physical Human-Robot Collaboration (HRC) between a robot holding the part and a human operator equipped with an abrasive tool. During the polishing task, the robot should firmly keep the workpiece in a prescribed sequence of poses, by monitoring and resisting to the external forces applied by the operator. However, the user may also wish to change the orientation of the part mounted on the robot, simply by pushing or pulling the robot body and changing thus its configuration. We propose a control algorithm that is able to distinguish the external torques acting at the robot joints in two components, one due to the polishing forces being applied at the end-effector level, the other due to the intentional physical interaction engaged by the human. The latter component is used to reconfigure the manipulator arm and, accordingly, its end-effector orientation. The workpiece position is kept instead fixed, by exploiting the intrinsic redundancy of this subtask. The controller uses a F/T sensor mounted at the robot wrist, together with our recently developed model-based technique (the residual method) that is able to estimate online the joint torques due to contact forces/torques applied at any place along the robot structure. In order to obtain a reliable residual, which is necessary to implement the control algorithm, an accurate robot dynamic model (including also friction effects at the joints and drive gains) needs to be identified first. The complete dynamic identification and the proposed control method for the human-robot collaborative polishing task are illustrated on a 6R UR10 lightweight manipulator mounting an ATI 6D sensor
Master-Slave Coordination Using Virtual Constraints for a Redundant Dual-Arm Haptic Interface
Programming robots for tasks involving force interaction is difficult, since both the knowledge of the task and the dynamics of the robots are necessary. An immersive haptic interface for task demonstration is proposed, where theoperator can sense and act through the robot. This is achieved by coupling two robotic systems with virtual constraints such that they have the same coordinates in the operational space disregarding a fixed offset. Limitations caused by the singular configurations or the reach of the robots are naturally reflected to either side as haptic feedback
Improving Dynamics Estimations and Low Level Torque Control Through Inertial Sensing
In 1996, professors J. Edward Colgate and Michael Peshkin invented the
cobots as robotic equipment safe enough for interacting with human workers.
Twenty years later, collaborative robots are highly demanded in the
packaging industry, and have already been massively adopted by companies
facing issues for meeting customer demands. Meantime, cobots are still
making they way into environments where value-added tasks require more
complex interactions between robots and human operators. For other applications
like a rescue mission in a disaster scenario, robots have to deal with
highly dynamic environments and uneven terrains. All these applications
require robust, fine and fast control of the interaction forces, specially in the
case of locomotion on uneven terrains in an environment where unexpected
events can occur. Such interaction forces can only be modulated through the
control of joint internal torques in the case of under-actuated systems which
is typically the case of mobile robots. For that purpose, an efficient low level
joint torque control is one of the critical requirements, and motivated the
research presented here. This thesis addresses a thorough model analysis of
a typical low level joint actuation sub-system, powered by a Brushless DC
motor and suitable for torque control. It then proposes procedure improvements
in the identification of model parameters, particularly challenging in
the case of coupled joints, in view of improving their control. Along with
these procedures, it proposes novel methods for the calibration of inertial
sensors, as well as the use of such sensors in the estimation of joint torques
The design and control of an actively restrained passive mechatronic system for safety-critical applications
Development of manipulators that interact closely with humans has been a focus of research in
fields such as robot-assisted surgery and haptic interfaces for many years. Recent introduction
of powered surgical-assistant devices into the operating theatre has meant that robot
manipulators have been required to interact with both patients and surgeons. Most of these
manipulators are modified industrial robots. However, the use of high-powered mechanisms in
the operating theatre could compromise safety of the patient, surgeon, and operating room staff.
As a solution to the safety problem, the use of actively restrained passive arms has been
proposed. Clutches or brakes at each joint are used to restrict the motion of the end-effector to
restrain it to a pre-defined region or path. However, these devices have only had limited success
in following pre-defined paths under human guidance.
In this research, three major limitations of existing passive devices actively restrained are
addressed. [Continues.
Spatial Formation Control
In this thesis, we study robust spatial formation control from several aspects. First, we study robust adaptive attitude synchronization for a network of rigid body agents using various attitude error functions defined on SO(3). Our results are particularly useful for networks with large initial attitude difference. We devise an adaptive geometric approach to cope with situations where the inertia matrices are not available for measurement. We use the Frobenius norm as a measure for the difference between the actual values of inertia matrices and their estimated values, to construct the individual adaptive laws of the agents. Compared to the previous methods for synchronization on SO(3) such as those which are based on quaternions, our proposed approach does not contain any attitude representation ambiguity. As the final part of our studies from the attitude synchronization aspect, we analyze robustness to external disturbances and unmodeled dynamics, and propose a method to attenuate such effects. Simulation results illustrate the effectiveness of the proposed approach. In the next part of the thesis, we study the distributed localization of the extremum point of unknown quadratic functions representing various physical or artificial signal potential fields. It is assumed that the value of such functions can be measured at each instant. Using high pass filtering of the measured signals, a linear parametric model is obtained for system identification. For design purposes, we add a consensus term to modify the identification subsystem. Next, we analyze the exponential convergence of the proposed estimation scheme using algebraic graph theory. In addition, we derive a distributed identifiability condition and use it for the construction of distributed extremum seeking control laws. In particular, we show that for a network of connected agents, if each agent contains a portion of the dithering signals, it is still possible to drive the system states to the extremum point provided that the distributed identifiability condition is satisfied. In the final part of this research, several robust control problems for general linear time invariant multi-agent systems are studied. We consider the robust consensus problem in the presence of unknown Lipschitz nonlinearities and polytopic uncertainties in the model of each agent. Next, this problem is solved in the presence of external disturbances. A set of control laws is proposed for the network to attain the consensus task and under the zero initial condition, achieves the desired H-infinity performance. We show that by implementing the modified versions of these control laws, it is possible to perform two-time scales formation control
- …