Effect of force feedback on a bulldozer-type robot

Minamoto, Masahiko; Kawashima, Kenji; Kanno, Takahiro

doi:10.1109/icma.2016.7558908

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…Here, we exploit the unique twisted boundary of the rolling LCE ribbons, as the analogous caterpillar treads that are often equipped in wheeled robots or vehicles ( 46 , 47 ), to reduce slipping on granular substrates. Our ribbon can self-roll on hot, flat, dry loose sand with both coarse and fine sand grains without getting stuck ( SI Appendix, Fig.…”

Section: Resultsmentioning

confidence: 99%

Twisting for soft intelligent autonomous robot in unstructured environments

Zhao

Chi

Hong

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

115

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Significance Autonomy is crucial for soft robotics that are constructed of soft materials. It remains challenging to create autonomous soft robots that can intelligently interact with and adapt to changing environments without external controls. To do so, it often requires an analogical soft “brain” that integrates on-board sensing, control, computation, and decision-making. Here, we report an autonomous soft robot embodied with physical intelligence for decision-making via adaptive soft body-environment interactions and snap-through instability, without integrated sensing and external controls. This study harnesses physical intelligence as a new paradigm for designing autonomous soft robots that can interact intelligently with their environments, thus potentially reducing the burdens on the conventional integrated sensing, control, computations, and decision-making systems in designing intelligent soft robots.

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Section: Resultsmentioning

confidence: 99%

Twisting for soft intelligent autonomous robot in unstructured environments

Zhao

Chi

Hong

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

115

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show abstract

“…And the experimental results testified the effectiveness of the method via installing the sensor systems on bulldozers for experiments. Minamoto and Kawashima (2016) upgraded a remote-controlled bulldozer, which transmits data to the control system through sensors installed on the blade to realize force feedback. To provide visual feedback, cameras are installed on the operation box and roof of the remote bulldozer robot.…”

Section: Path Planning For Automatic Earthwork Machinerymentioning

confidence: 99%

Complete coverage path planning and performance factor analysis for autonomous bulldozer

Zhou

Dou

et al. 2022

Journal of Field Robotics

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With the development of intelligent machinery, path planning of autonomous bulldozers plays an important role to solve the problems of efficiency in future construction sites. How to plan the path that meets the construction requirements is the key problem. This study investigates the standardized construction workmanship and moving rules of the bulldozer to add rules and path selection strategies to the algorithm. This study establishes the path planning model of bulldozer's leveling, considering the limitations of the traditional bioinspired neural network algorithm, an improved complete coverage path planning method is proposed. An integrated framework is proposed for an automatic bulldozer with a sensor system for a field experiment to verify the feasibility of the method. According to the comparative statistical simulation results, the effectiveness of the method is verified, and the effects of different factors on the path planning results are analyzed.

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“…A number of experiments were conducted in which the operator was able to operate the bulldozer safely and efficiently from a remote position. Recently, a teleoperated bulldozer with force feedback [49] was introduced by using sensors attached to the blade and transmitting data to the control system. Cameras were installed for visual feedback within and on the roof of the operator cabinet of the remotely-controlled bulldozer-type robot.…”

Section: Teleoperated Bulldozersmentioning

confidence: 99%

Robotic autonomous systems for earthmoving in military applications

Yen

Balaguer

2019

Automation in Construction

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Along with increasing innovations in frontier engineering sciences, the advancement in Robotic Autonomous Systems (RAS) has brought about a new horizon in earthmoving processes for construction. In the military domain, there is also an increasing interest in utilising RAS technologies. In particular, ground-based forces are frequently called upon to conduct earthmoving tasks as part of military operations, tasks which could be partially or fully aided by the employment of RAS technologies. There have been rapid developments in military construction automation using high-mobility ground-based platforms, human-machine and machine-machine interfaces, teleoperation and control systems, data transmission systems, machine perception and manipulation capabilities, as well as advances in networked robotics and cyberphysical systems. Given these developments it is timely to undertake a comprehensive overview on the topic of interest to the research community and the authority. This paper presents an overview of the RAS development for platform-centric earthworks together with an analysis of the technical feasibility, maturity, key technical challenges, and future directions for the application of RAS technologies to earthmoving tasks of interest to the army. KeywordsMilitary earthmoving; robotic autonomous systems; technology/system readiness; mode of control 2.2.1Perception Robotic perception represents the sensing and data processing required of an autonomous system to acquire and represent knowledge about its environment. That is, to obtain measurements using various appropriate sensors, to extract meaningful information from those measurements, and to represent the environment in the form of a model that can be updated and interrogated.

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Effect of force feedback on a bulldozer-type robot

Cited by 5 publications

References 4 publications

Twisting for soft intelligent autonomous robot in unstructured environments

Twisting for soft intelligent autonomous robot in unstructured environments

Complete coverage path planning and performance factor analysis for autonomous bulldozer

Robotic autonomous systems for earthmoving in military applications

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