A fault-tolerant intelligent robotic control system

This paper describes the concept, design, and features of a fault-tolerant intelligent robotic control system being developed for space and commercial applications that require high dependability. The comprehensive strategy integrates system level hardware/software fault tolerance with task level handling of uncertainties and unexpected events for robotic control. The underlying architecture for system level fault tolerance is the distributed recovery block which protects against application software, system software, hardware, and network failures. Task level fault tolerance provisions are implemented in a knowledge-based system which utilizes advanced automation techniques such as rule-based and model-based reasoning to monitor, diagnose, and recover from unexpected events. The two level design provides tolerance of two or more faults occurring serially at any level of command, control, sensing, or actuation. The potential benefits of such a fault tolerant robotic control system include: (1) a minimized potential for damage to humans, the work site, and the robot itself; (2) continuous operation with a minimum of uncommanded motion in the presence of failures; and (3) more reliable autonomous operation providing increased efficiency in the execution of robotic tasks and decreased demand on human operators for controlling and monitoring the robotic servicing routines

Contact detection and contact motion for error recovery in the presence of uncertainties

Due to various kinds of uncertainties, a robot motion may fail and result in some unintended contact between the object held by the robot and the environment, which greatly hampers robotics applications on tasks with high-precision requirements, such as assembly tasks. Aiming at automatically recovering a robotic task from such a failure, this paper discusses, in the presence of uncertainties, contact detection based on contact motion for recovery. It presents a framework for on-line recognizing contacts using multiple sensor modalities in the presence of sensing uncertainties and means for ensuring successful compliant motions in the presence of sensing and control uncertainties

Autonomous Mechanical Assembly on the Space Shuttle: An Overview

The space shuttle will be equipped with a pair of 50 ft. manipulators used to handle payloads and to perform mechanical assembly operations. Although current plans call for these manipulators to be operated by a human teleoperator. The possibility of using results from robotics and machine intelligence to automate this shuttle assembly system was investigated. The major components of an autonomous mechanical assembly system are examined, along with the technology base upon which they depend. The state of the art in advanced automation is also assessed

Robotic assembly of complex planar parts: An experimental evaluation

In this paper we present an experimental evaluation of automatic robotic assembly of complex planar parts. The torque-controlled DLR light-weight robot, equipped with an on-board camera (eye-in-hand configuration), is committed with the task of looking for given parts on a table, picking them, and inserting them inside the corresponding holes on a movable plate. Visual servoing techniques are used for fine positioning over the selected part/hole, while insertion is based on active compliance control of the robot and robust assembly planning in order to align the parts automatically with the hole. Execution of the complete task is validated through extensive experiments, and performance of humans and robot are compared in terms of overall execution time

The application of a pilot pull planning system to construction projects

A new planning system was introduced as a pilot within a large UK construction company. The system, which attempts to address some of the problems of construction “front end” planning, is investigated relative to Lean Construction and specifically the Last Planner system. The purpose is to see if it can be used as the basis for applying a lean planning model which the company intends to introduce and test through a research project. The existing system is seen to have strengths in terms of goodwill and commitment from the participants but is still fundamentally linked to the schedule pushed traditional approach to planning which is seen to be unsuccessful. An attempt to use “first run studies” to produce high quality planning and performance information was partly successful and indicated possibilities for future implementation. Further work is needed to fully develop the application model and training in the fundamentals of the system will be needed to improve performance

Collaborative and Cooperative Robotics Applications using Visual Perception

The objective of this Thesis is to develop novel integrated strategies for collaborative and cooperative robotic applications. Commonly, industrial robots operate in structured environments and in work-cell separated from human operators. Nowadays, collaborative robots have the capacity of sharing the workspace and collaborate with humans or other robots to perform complex tasks. These robots often operate in an unstructured environment, whereby they need sensors and algorithms to get information about environment changes. Advanced vision and control techniques have been analyzed to evaluate their performance and their applicability to industrial tasks. Then, some selected techniques have been applied for the first time to an industrial context. A Peg-in-Hole task has been chosen as first case study, since it has been extensively studied but still remains challenging: it requires accuracy both in the determination of the hole poses and in the robot positioning. Two solutions have been developed and tested. Experimental results have been discussed to highlight the advantages and disadvantages of each technique. Grasping partially known objects in unstructured environments is one of the most challenging issues in robotics. It is a complex task and requires to address multiple subproblems, in order to be accomplished, including object localization and grasp pose detection. Also for this class of issues some vision techniques have been analyzed. One of these has been adapted to be used in industrial scenarios. Moreover, as a second case study, a robot-to-robot object handover task in a partially structured environment and in the absence of explicit communication between the robots has been developed and validated. Finally, the two case studies have been integrated in two real industrial setups to demonstrate the applicability of the strategies to solving industrial problems