Compliant and stable robot control for physical human-robot cooperation

The main goal of this thesis is to accomplish a compliant and stable closed-loop physical human-robot cooperation by guaranteeing the safety metrics for all of the agents in a shared-working environment. There is increasing interest in control frameworks capable of moving robots from industrial cages to unstructured environments and coexisting with humans. Initially, having robots capable of safely interacting with humans was of interest for medical applications (e.g., rehabilitation, surgical). Despite significant improvement in some specific applications like medical robotics, there is still the need for a general control framework that improves interaction robustness and motion dynamics. Passive controllers show promising results in this direction; however, they often rely on virtual energy tanks that can guarantee passivity as long as they do not run out of energy. In this thesis, a fractal attractor is proposed to implement a variable impedance controller that can retain passivity without relying on energy tanks. The controller generates a fractal attractor around the desired state using an asymptotic stable potential field, making the controller robust to discretization and numerical integration errors. Thus, the proposed Fractal Impedance Controller (FIC) in this thesis is robust for low-bandwidth applications. I have tested this controller with a torque controlled 7-DoF manipulator. The results prove that it can accurately track both trajectories and end-effector forces during interaction. Furthermore, it can automatically deal with the extra energy introduced by changes in interaction conditions, null-space controller and environment. Therefore, on the one hand these properties make the controller ideal for applications where the dynamic interaction at the end-effector is challenging to be characterized a priori, such as proximate physical human-robot cooperation and unknown dynamics. On the other hand in remote human-robot cooperation, robotic teleoperation provides human-in-the-loop capabilities of complex manipulation tasks in dangerous or remote environments, such as planetary exploration or nuclear decommissioning. This thesis proposes a novel bilateral telemanipulation architecture using the proposed passive FIC, which does not depend upon an active viscous component for guaranteeing stability. Compared to a traditional impedance controller in ideal conditions (no delays and maximum communication bandwidth), the proposed method yields higher transparency in interaction and demonstrates superior dexterity and capability in my telemanipulation test scenarios. I also validate its performance with extreme delays up to 1s and communication bandwidths as low as 10Hz. The results of the carried out experiments validate a consistent stability when using the proposed controller in challenging conditions, regardless of operator expertise. The proposed fractal impedance controller in this thesis exploits its non-linear stiffness to adapt to multiple cooperative scenarios without tuning the controller. Furthermore, the FIC has an intuitive method to adjust the impedance that can be performed online without affecting stability. The experimental results, carried out using 2 torque controlled 7-DoF manipulators and the Sigma.7 haptic device, also show that the proposed method can perform tasks such as drilling, moving objects with unknown dynamics, and interacting with humans without re-tuning the controller's impedance in a tele-cooperative manner consisting of multi-agents in the loop. The FIC also allows identifying the highest impedance profile for a robot experimentally, and it bounds the maximum momentum generated while moving. Thus, it opens new possibilities for developing better adaptive controllers by coupling the proposed method with learning and optimisation algorithms to modulate its behaviour without the risk of incurring instability issues.YOUTUBE links to Chapters 3,4 & 5 below

Safety Awareness for Rigid and Elastic Joint Robots: An Impact Dynamics and Control Framework

This thesis aims at making robots with rigid and elastic joints aware of human collision safety. A framework is proposed that captures human injury occurrence and robot inherent safety properties in a unified manner. It allows to quantitatively compare and optimize the safety characteristics of different robot designs and is applied to stationary and mobile manipulators. On the same basis, novel motion control schemes are developed and experimentally validated

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

The Shape of Damping: Optimizing Damping Coefficients to Improve Transparency on Bilateral Telemanipulation

This thesis presents a novel optimization-based passivity control algorithm for hapticenabled bilateral teleoperation systems involving multiple degrees of freedom. In particular, in the context of energy-bounding control, the contribution focuses on the implementation of a passivity layer for an existing time-domain scheme, ensuring optimal transparency of the interaction along subsets of the environment space which are preponderant for the given task, while preserving the energy bounds required for passivity. The involved optimization problem is convex and amenable to real-time implementation. The effectiveness of the proposed design is validated via an experiment performed on a virtual teleoperated environment. The interplay between transparency and stability is a critical aspect in haptic-enabled bilateral teleoperation control. While it is important to present the user with the true impedance of the environment, destabilizing factors such as time delays, stiff environments, and a relaxed grasp on the master device may compromise the stability and safety of the system. Passivity has been exploited as one of the the main tools for providing sufficient conditions for stable teleoperation in several controller design approaches, such as the scattering algorithm, timedomain passivity control, energy bounding algorithm, and passive set position modulation. In this work it is presented an innovative energy-based approach, which builds upon existing time-domain passivity controllers, improving and extending their effectiveness and functionality. The set of damping coefficients are prioritized in each degree of freedom, the resulting transparency presents a realistic force feedback in comparison to the other directions. Thus, the prioritization takes effect using a quadratic programming algorithm to find the optimal values for the damping. Finally, the energy tanks approach on passivity control is a solution used to ensure stability in a system for robotics bilateral manipulation. The bilateral telemanipulation must maintain the principle of passivity in all moments to preserve the system\u2019s stability. This work presents a brief introduction to haptic devices as a master component on the telemanipulation chain; the end effector in the slave side is a representation of an interactive object within an environment having a force sensor as feedback signal. The whole interface is designed into a cross-platform framework named ROS, where the user interacts with the system. Experimental results are presented

Kinesthetic Haptics Sensing and Discovery with Bilateral Teleoperation Systems

In the mechanical engineering field of robotics, bilateral teleoperation is a classic but still increasing research topic. In bilateral teleoperation, a human operator moves the master manipulator, and a slave manipulator is controlled to follow the motion of the master in a remote, potentially hostile environment. This dissertation focuses on kinesthetic perception analysis in teleoperation systems. Design of the controllers of the systems is studied as the influential factor of this issue. The controllers that can provide different force tracking capability are compared using the same experimental protocol. A 6 DOF teleoperation system is configured as the system testbed. An innovative master manipulator is developed and a 7 DOF redundant manipulator is used as the slave robot. A singularity avoidance inverse kinematics algorithm is developed to resolve the redundancy of the slave manipulator. An experimental protocol is addressed and three dynamics attributes related to kineshtetic feedback are investigated: weight, center of gravity and inertia. The results support our hypothesis: the controller that can bring a better force feedback can improve the performance in the experiments

Safe Haptics-enabled Patient-Robot Interaction for Robotic and Telerobotic Rehabilitation of Neuromuscular Disorders: Control Design and Analysis

Motivation: Current statistics show that the population of seniors and the incidence rate of age-related neuromuscular disorders are rapidly increasing worldwide. Improving medical care is likely to increase the survival rate but will result in even more patients in need of Assistive, Rehabilitation and Assessment (ARA) services for extended periods which will place a significant burden on the world\u27s healthcare systems. In many cases, the only alternative is limited and often delayed outpatient therapy. The situation will be worse for patients in remote areas. One potential solution is to develop technologies that provide efficient and safe means of in-hospital and in-home kinesthetic rehabilitation. In this regard, Haptics-enabled Interactive Robotic Neurorehabilitation (HIRN) systems have been developed. Existing Challenges: Although there are specific advantages with the use of HIRN technologies, there still exist several technical and control challenges, e.g., (a) absence of direct interactive physical interaction between therapists and patients; (b) questionable adaptability and flexibility considering the sensorimotor needs of patients; (c) limited accessibility in remote areas; and (d) guaranteeing patient-robot interaction safety while maximizing system transparency, especially when high control effort is needed for severely disabled patients, when the robot is to be used in a patient\u27s home or when the patient experiences involuntary movements. These challenges have provided the motivation for this research. Research Statement: In this project, a novel haptics-enabled telerobotic rehabilitation framework is designed, analyzed and implemented that can be used as a new paradigm for delivering motor therapy which gives therapists direct kinesthetic supervision over the robotic rehabilitation procedure. The system also allows for kinesthetic remote and ultimately in-home rehabilitation. To guarantee interaction safety while maximizing the performance of the system, a new framework for designing stabilizing controllers is developed initially based on small-gain theory and then completed using strong passivity theory. The proposed control framework takes into account knowledge about the variable biomechanical capabilities of the patient\u27s limb(s) in absorbing interaction forces and mechanical energy. The technique is generalized for use for classical rehabilitation robotic systems to realize patient-robot interaction safety while enhancing performance. In the next step, the proposed telerobotic system is studied as a modality of training for classical HIRN systems. The goal is to first model and then regenerate the prescribed kinesthetic supervision of an expert therapist. To broaden the population of patients who can use the technology and HIRN systems, a new control strategy is designed for patients experiencing involuntary movements. As the last step, the outcomes of the proposed theoretical and technological developments are translated to designing assistive mechatronic tools for patients with force and motion control deficits. This study shows that proper augmentation of haptic inputs can not only enhance the transparency and safety of robotic and telerobotic rehabilitation systems, but it can also assist patients with force and motion control deficiencies

Stability and Performance Improvement in Haptic Human-Robot Interaction

The goal of this research is to develop theories, methods, and tools to understand the mechanisms of neuromotor adaptation in human-robot physical interaction, in order to improve the stability and performance of the interaction. Human power-assisting systems (e.g., powered lifting devices that aid human operators in manipulating heavy or bulky loads) require physical contact between the operator and machine, creating a coupled dynamic system. This dynamic coupling has been shown to introduce inherent instabilities and performance degradation due to a change in human stiffness; when instability is encountered, a human operator often attempts to control the oscillation by stiffening their arm, which leads to a stiffer system with more instability. Robot co-worker controllers must account for this issue. In this work we set out to 1) understand the association between neuromuscular adaptations and system performance limits, 2) develop probabilistic methods to classify and predict the transition of operator’s cognitive and physical states from physiological measures, and 3) integrate this knowledge into a structure of shared human-robot control. We developed a model of the human operator endpoint stiffness, characterized at the musculoskeletal level, that can account for deliberate stiffness increase at the endpoint through the incorporation of muscle coactivation. We also developed a switching admittance control approach which can account for changes in the operator’s muscle coactivation and is able to generate cognitive states in an unsupervised manner, given a relevant training dataset. Finally, a novel variable admittance control approach, which significantly reduces grasp contact instability commonly encountered in fixed admittance control settings, was developed, analytically derived, and provides solutions for both constant mass and variable mass parameter cases.Ph.D