Fault-tolerant Robot Research Articles

Review of Fault-Tolerant Control Systems Used in Robotic Manipulators

Control systems that ensure robot operation during failures are necessary, particularly when manipulators are operating in hazardous or hard-to-reach environments. In such applications, fault-tolerant robot controllers should detect failures and, using fault-tolerant control methods, be able to continue operation without human intervention. Fault-tolerant control (FTC) is becoming increasingly important in all industries, including production lines in which modern robotic manipulators are used. The use of fault-tolerant systems in robotics can prevent the production line from being immobilized due to minor faults. In this paper, an overview of the current state-of-the-art methods of fault-tolerant control in robotic manipulators is provided. This review covers publications from 2003 to 2022. The article pays special attention to the use of artificial intelligence (AI), i.e., fuzzy logic and artificial neural networks, as well as sliding mode and other control methods, in the FTC of robotic manipulators. The cited and described publications were mostly found using Google Scholar.

Flies trade off stability and performance via adaptive compensation to wing damage.

Physical injury often impairs mobility, which can have dire consequences for survival in animals. Revealing mechanisms of robust biological intelligence to prevent system failure can provide critical insights into how complex brains generate adaptive movement and inspiration to design fault-tolerant robots. For flying animals, physical injury to a wing can have severe consequences, as flight is inherently unstable. Using a virtual reality flight arena, we studied how flying fruit flies compensate for damage to one wing. By combining experimental and mathematical methods, we show that flies compensate for wing damage by corrective wing movement modulated by closed-loop sensing and robust mechanics. Injured flies actively increase damping and, in doing so, modestly decrease flight performance but fly as stably as uninjured flies. Quantifying responses to injury can uncover the flexibility and robustness of biological systems while informing the development of bio-inspired fault-tolerant strategies.

An Algorithm to Design Redundant Manipulators of Optimally Fault-Tolerant Kinematic Structure

One measure of the global fault tolerance of a redundant robot is the size of its self-motion manifold. If this size is defined as the range of its joint angles, then the optimal self-motion manifold size for an n-degree-of-freedom (DoF) robot is n × 2π, which is not typical for existing robot designs. This letter presents a novel two-step algorithm to optimize the kinematic structure of a redundant manipulator to have an optimal self-motion manifold size. The algorithm exploits the fact that singularities occur on large self-motion manifolds by optimizing the robots kinematic parameters around a singularity. Because a gradient for the self-motion manifold size does not exist, the kinematic parameter optimization uses a coordinate descent procedure. The algorithm was used to design 4-DoF, 7-DoF, and 8-DoF manipulators to illustrate its efficacy at generating optimally fault-tolerant robots of any kinematic structure.

Maximizing the Size of Self-Motion Manifolds to Improve Robot Fault Tolerance

One measure of a robot's fault tolerance is the size of its self-motion manifold. This letter presents a new methodology for finding the largest self-motion manifold(s) of kinematically redundant robots, that consists of two algorithms. Because large self-motion manifolds occur near singular configurations, the first algorithm is designed to identify singularities of all ranks, including high-rank singularities. One unique feature of this algorithm is its ability to deal with the ill conditioned nature of singular vectors when there are multiple nearly equal singular values. The second algorithm is constructed to compute the self-motion manifolds that contain these singular configurations by iteratively moving along the null space of the robot's Jacobian. An important aspect of this computation is to deal with singularities along the manifold, where the null space is high dimensional. These two algorithms are applied to the well-known Mitsubishi PA-10 to illustrate their effectiveness at identifying singularities and computing the largest self-motion manifold(s).

QR Code-Based Self-Calibration for a Fault-Tolerant Industrial Robot Arm

Malfunctions on industrial robots can cost factories 22000 dollars per minute. Although the benefits of a fault-tolerant robot arm are clear, redundant sensors would steeply add to the costs of such robots while machine learning-based methods would spend too much time learning the robot's model. We propose a simple but highly effective method to infer which joint underwent failure and at which angle this joint is constrained and to, then, modify the inverse kinematics (IK) algorithm to adaptively achieve the goal. Our method involves combining the robot arm with a QR code and an inexpensive camera, building a virtual link between these three to give the relative position of the end-effector. Once one joint/encoder/motor suffers damage, we use this virtual link to calibrate this joint by coordinate transformation, to calculate the constrained angle, and to recalculate the trajectory through IK iterations with the Newton-Raphson method. We prove the efficacy of our method with pick-and-place experiments, commonly seen in industrial settings, emulating malfunctions on different joints and at different angles, and our method can successfully finish the task in most cases. We further demonstrate that our method is capable, for almost all of the six-degree-of-freedom manipulators, to adapt to joint failures after suffering an actuator failure. With the steep increase of robots within factories, this paper presents an elegant approach to keep robots functional until maintenance is scheduled, reducing downtime.

Kinematic Design of Optimally Fault Tolerant Robots for Different Joint Failure Probabilities

A measure of fault tolerance for different joint failure probabilities is defined based on the properties of the singular values of the Jacobian after failures. Using this measure, methods to design optimally fault tolerant robots for an arbitrary set of joint failure probabilities and multiple cases of joint failure probabilities are introduced separately. Given an arbitrary set of joint failure probabilities, the optimal null space that optimizes the fault tolerant measure is derived, and the associated isotropic Jacobians are constructed. The kinematic parameters of the optimally fault tolerant robots are then generated from these Jacobians. One special case, i.e., how to construct the optimal Jacobian of spatial 7R robots for both positioning and orienting is further discussed. For multiple cases of joint failure probabilities, the optimal robot is designed through optimizing the sum of the fault tolerant measures for all the possible joint failure probabilities. This technique is illustrated on planar 3R robots, and it is shown that there exists a family of optimal robots.

Design and control of tensegrity robots for locomotion

The static properties of tensegrity structures have been widely appreciated in civil engineering as the basis of extremely lightweight yet strong mechanical structures. However, the dynamic properties and their potential utility in the design of robots have been relatively unexplored. This paper introduces robots based on tensegrity structures, which demonstrate that the dynamics of such structures can be utilized for locomotion. Two tensegrity robots are presented: TR3, based on a triangular tensegrity prism with three struts, and TR4, based on a quadrilateral tensegrity prism with four struts. For each of these robots, simulation models are designed, and automatic design of controllers for forward locomotion are performed in simulation using evolutionary algorithms. The evolved controllers are shown to be able to produce static and dynamic gaits in both robots. A real-world tensegrity robot is then developed based on one of the simulation models as a proof of concept. The results demonstrate that tensegrity structures can provide the basis for lightweight, strong, and fault-tolerant robots with a potential for a variety of locomotor gaits

Fault-Tolerant Robot Programming through Simulation with Realistic Sensor Models

We introduce a simulation system for mobile robots that allows a realistic interaction of multiple robots in a common environment. The simulated robots are closely modeled after robots from the EyeBot family and have an identical application programmer interface. The simulation supports driving commands at two levels of abstraction as well as numerous sensors such as shaft encoders, infrared distance sensors, and compass. Simulation of on-board digital cameras via synthetic images allows the use of image processing routines for robot control within the simulation. Specific error models for actuators, distance sensors, camera sensor, and wireless communication have been implemented. Progressively increasing error levels for an application program allows for testing and improving its robustness and fault-tolerance.

Fault tolerance versus performance metrics for robot systems

The incorporation of fault tolerance techniques into robot systems improves the reliability, but also increases the hardware and computational requirements in the overall system. It is not always clear how to evaluate the merit, or ‘effectiveness’ of different fault tolerance approaches for a given application. In this paper, we present a new set of performance criteria designed to measure and compare the effectiveness of robot fault tolerance strategies. The measures, which are designed to evaluate fault tolerance/performance/cost tradeoffs, can also be used to evaluate pure performance or pure fault tolerance strategies. We show their usefulness using a variety of proposed fault tolerance approaches in the literature, focusing on multiprocessor control architectures.

Implementations of a four-level mechanical architecture for fault-tolerant robots

This paper describes a fault tolerant mechanical architecture with four levels devised and implemented in concert with NASA (Tesar, D. & Sreevijayan, D., Four-level fault tolerance in manipulator design for space operations. In First Int. Symp. Measurement and Control in Robotics ( ISMCR '90), Houston, Texas, 20–22 June 1990.) Subsequent work has clarified and revised the architecture. The four levels proceed from fault tolerance at the actuator level, to fault tolerance via in-parallel chains, to fault tolerance using serial kinematic redundancy, and finally to the fault tolerance multiple arm systems provide. This is a subsumptive architecture because each successive layer can incorporate the fault tolerance provided by all layers beneath. For instance a serially-redundant robot can incorporate dual fault-tolerant actuators. Redundant systems provide the fault tolerance, but the guiding principle of this architecture is that functional redundancies actively increase the performance of the system. Redundancies do not simply remain dormant until needed. This paper includes specific examples of hardware and/or software implementation at all four levels.

A Graphic Simulation Tool for Fault Diagnosis in Robots

This work describes a graphic simulation tool for analysis and design of a fault tolerant robot. As a general rule one of the first steps in designing fault-tolerant systems is to analyse the system in order to point out the various faults that can occur in all parts of the system. To reach this goal, good knowledge of the system is required and simulation tools are then of great use, especially as it is uneasy to study the effect of fault on a real system. Moreover, graphic interfaces can give a correct simulation of the modification of the system in its structure.

Helenic fault tolerance for robots

In robot applications where the consequences of system failure are unbearable, fault tolerance is mandatory. Fault tolerant robots continue to function correctly despite component failures. Fault tolerant robots can be designed using the Helenic architecture. This architecture uses non-homogeneous functional modular redundancy and a democratic dynamic weighted voting algorithm for redundancy management to achieve fault tolerance. The benefits offered are increased reliability, maintainability, common mode failure resistance, and significant cost reductions. To demonstrate the fault tolerance capabilities of this system architecture, a 5 wheel omnidirectional mobile robot with sensors, computing elements and actuators was designed and simulated. Simulation results verify the robot's ability to continue ‘correct’ operation despite internal subsystem failures.

Robotic fault detection and fault tolerance: A survey

Abstract Fault tolerance is increasingly important for robots, especially those in remote or hazardous environments. Robots need the ability to effectively detect and tolerate internal failures in order to continue performing their tasks without the need for immediate human intervention. Recently, there has been a surge of interest in robot fault tolerance, and the subject has been investigated from a number of points of view. Ongoing research performs off-line and on-line failure analyses of robotic systems, develops fault-tolerant control environments, and derives fault detection and error recovery techniques using hardware, kinematic, or functional redundancy. This paper presents a summary of the current, limited, state-of-the-art in fault-tolerant robotics and offers some future possibilities for the field.

Fault-tolerant joint development for the Space Shuttle remote manipulator system: analysis and experiment

The feasibility of space-based fault-tolerant robot joint design with a dual-motor, single-output differential-based mechanical drive system is investigated. The mathematical model of the differential system is developed, and the inherent nonlinear dynamic characteristics for the differential are reduced to linear state equations through variable substitutions. Nonlinear phenomena such as gearbox forward/backdrive efficiency, motor friction/stiction, and torque limiting are included. Simulations have been performed for various joint failure conditions. A scaled-down differential testbed has been designed and built to validate the analytical results. Simulation and test results demonstrate that the design is capable of sustaining a single failure and absorbing the failure disturbance, and continuing to be operational with the remaining single drive mode. >

A control architecture for an advanced fault-tolerant robot system

A major issue in robotic research is the development of advanced autonomous robots which are able to solve a difficult task in a complex environment. Besides the need for powerful sensing and planning capabilities, an autonomous system must incorporate a highly sophisticated control architecture. This paper describes an advanced robot control system which is being developed at the Institute for Real-Time Computer Control Systems and Robotics of the University of Karlsrube. As a test environment for the implementation of this architecture, the autonomous moible two-arm robot system KAMRO is used.

A concept for an intelligent and fault-tolerant robot system

A concept for the intelligent control of subsystems of a flexible assembly cell is presented. Unknown or uncertain data about the real world may lead towards failure during an assembly task. Therefore, a fault tolerant system must be capable of reacting immediately to error situations. Thus, the major topic of this paper is the dynamic handling of unforeseen situations during realtime activities. This will be achieved by combining sensor guided actions with an advanced autonomous supervision system. Experimental results will be derived from the mobile two-arm robot system KAMRO of the Institute for Real-Time Computer Control Systems and Robotics, University of Karlsruhe, Federal Republic of Germany.