Marker-based pose estimation, in which optical cameras monitor fiducial markers to determine the three-dimensional positioning and orientation of an articulated machine's end effector, has been identified as a potential low-cost alternative to currently available machine control and guidance systems. In an effort to develop such a marker-based pose estimation system for excavators, several iterations of prototypes were designed, fabricated, and tested. Performance was measured in terms of the system's ability to estimate bucket tooth position, with an acceptance criterion of 2.5 centimeters (1 inch) of absolute error. Although initial prototypes were found to possess practicality and performance issues, a fourth prototype offered encouraging experimental results suggesting the feasibility of marker-based sensor technology for excavator pose estimation. Further work needed to refine the technology for large-scale practical implementation was also identified.
Compared to widespread successful deployment of robotic manipulators for repetitive and hazardous tasks in related industries such as manufacturing, the construction industry has achieved relatively limited benefits from robotics and soft automation. Unlike manufacturing, where robotic solutions benefit from the structured layout of the environment (e.g., factory assembly line), construction robots face unique challenges that arise from the rugged, dynamic, and unstructured environment of the work site, as well as the uncertainty and evolving sequence of occurring on-site events. This challenges any intended construction robots to not only replicate basic human motion, but also be capable of sensing and adapting to environmental changes, and making decisions based on the evolving state of the environment. Building upon recent advancements in robotic mapping, computer vision, and object recognition, the authors propose to introduce autonomous behavior at the basic task level for on-site construction robots to address these challenges in a flexible and extensible manner. This paper reports the outcome of the first phase of this research -a structured methodology for improved design and development of basic task automations -and focuses on algorithms developed for mobile robot navigation and relative pose estimation. The algorithms are implemented on a prototype mobile robotic platform, and evaluated in several experimental scenarios.
Vision-based pose estimation, in which optical cameras monitor fiducial markers to determine the three dimensional positioning and orientation of an articulated machine's end effector, offers a promising low-cost alternative to currently available sensor packages that are non-ubiquitous and cost prohibitive for a large portion of the market. Whereas traditional sensor systems determine end effector pose via kinematic chains passing through the links of a machine, optical sensor systems are capable of determining pose by observing an end effector directly. However, since markers cannot be mounted on an excavator's bucket for occlusion and durability reasons, a short kinematic chain must be used. An electromechanical design is proposed to provide such function for a low cost marker-based excavator pose estimation system. Several iterations of design and experimentation are discussed, including a four-bar linkage system, a synchronous belt system, a bucket linkage system, and a cable potentiometer system. The four-bar linkage and toothed belt systems were designed to transmit bucket angle information to cameras through the manipulation of a marker's pose, but were found to possess Gimbal lock and practicality issues, respectively. To overcome such issues, a generalized mapping approach was adopted and implemented in a bucket linkage design and a cable potentiometer design. The viability of the cable potentiometer system was experimentally confirmed, along with the identification of further work needed to refine the technology for large-scale practical implementation.
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