Stair Climbing Robots and High-Grip Crawler

Yoneda, Kan; Ota, Yusuke; Hirose, Shigeo

doi:10.5772/8843

Cited by 5 publications

(8 citation statements)

References 27 publications

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“…Commercial solution, autonomous driving, self-balancing control system, soft rubber tracks Yoneda [59] Robotics 2023, 12, x FOR PEER REVIEW 14 of 45…”

Section: Name Solution Featuresmentioning

confidence: 99%

“…The NWC of carrier type robots is presented in Figure 5. [68]; iRobot 710 Kobra [63]; Haulerbot [62]; HELIOS-VI [61]; TAQT Carrier [60]; Yoneda [59].…”

Section: Ns =mentioning

confidence: 99%

“…As seen from the bar charts, the NWC metric well defines the different robot categories The NWC of carrier type robots is presented in Figure 5. [68]; iRobot 710 Kobra [63]; Haulerbot [62]; HELIOS-VI [61]; TAQT Carrier [60]; Yoneda [59].…”

Section: Ns =mentioning

confidence: 99%

“…A graphical representation of the maximum crossable height and slope is given below. Figure 6 refers to wheelchair-type robots while Figure 7 refers [68]; iRobot 710 Kobra [63]; Haulerbot [62]; HELIOS-VI [61]; TAQT Carrier [60]; Yoneda [59].…”

Section: Ns =mentioning

confidence: 99%

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Watch the Next Step: A Comprehensive Survey of Stair-Climbing Vehicles

Pappalettera,

Bottiglione,

Mantriota

et al. 2023

Robotics

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Stair climbing is one of the most challenging tasks for vehicles, especially when transporting people and heavy loads. Although many solutions have been proposed and demonstrated in practice, it is necessary to further improve their climbing ability and safety. This paper presents a systematic review of the scientific and engineering stair climbing literature, providing brief descriptions of the mechanism and method of operation and highlighting the advantages and disadvantages of different types of climbing platform. To quantitatively evaluate the system performance, various metrics are presented that consider allowable payload, maximum climbing speed, maximum crossable slope, transport ability and their combinations. Using these metrics, it is possible to compare vehicles with different locomotion modes and properties, allowing researchers and practitioners to gain in-depth knowledge of stair-climbing vehicles and choose the best category for transporting people and heavy loads up a flight of stairs.

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“…Commercial solution, autonomous driving, self-balancing control system, soft rubber tracks Yoneda [59] Robotics 2023, 12, x FOR PEER REVIEW 14 of 45…”

Section: Name Solution Featuresmentioning

confidence: 99%

“…The NWC of carrier type robots is presented in Figure 5. [68]; iRobot 710 Kobra [63]; Haulerbot [62]; HELIOS-VI [61]; TAQT Carrier [60]; Yoneda [59].…”

Section: Ns =mentioning

confidence: 99%

Section: Ns =mentioning

confidence: 99%

Section: Ns =mentioning

confidence: 99%

See 2 more Smart Citations

Watch the Next Step: A Comprehensive Survey of Stair-Climbing Vehicles

Pappalettera,

Bottiglione,

Mantriota

et al. 2023

Robotics

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“…They are better suited for such tasks than wheeled vehicles due to the larger contact area of tracks with the ground, which provides better traction on harsh terrain. The high degree of mobility of these robots strictly depends on the locomotion mechanics design (Blackburn, Bailey, & Lytle, ; Freitas, Gleizer, Lizarralde, Hsu, & dos Reis, ; Grand, Ben Amar, & Bidaud, ; Thueer & Siegwart, ; Wang & Gu, ; Yoneda, Ota, & Hirose, ). In the past few decades, research studies on mobility led to the design of many degrees of freedom (DOF) AATVs, such as ROBHAZ‐DT3 (Lee et al., ), Kenaf (Yoshida et al., ), HELIOS (Guarnieri et al., ), and Quince (Rohmer et al., ).…”

Section: Introduction and Motivationsmentioning

confidence: 99%

Adaptive Robust Three-dimensional Trajectory Tracking for Actively Articulated Tracked Vehicles*

et al. 2015

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A new approach is proposed for an adaptive robust three-dimensional (3D) trajectory-tracking controller design. The controller is modeled for actively articulated tracked vehicles (AATVs). These vehicles have active subtracks, called flippers, linked to the ends of the main tracks, to extend the locomotion capabilities in hazardous environments, such as rescue scenarios. The proposed controller adapts the flippers configuration and simultaneously generates the track velocities, to allow the vehicle to autonomously follow a given feasible 3D path. The approach develops both a direct and differential kinematic model of the AATV for traversal task execution correlating the robot body motion to the flippers motion. The benefit of this approach is to allow the controller to flexibly manage all the degrees of freedom of the AATV as well as the steering. The differential kinematic model integrates a differential drive robot model, compensating the slippage between the vehicle tracks and the traversed terrain. The underlying feedback control law dynamically accounts for the kinematic singularities of the mechanical vehicle structure. The designed controller integrates a strategy selector too, which has the role of locally modifying the rail path of the flipper end points. This serves to reduce both the effort of the flipper servo motors and the traction force on the robot body, recognizing when the robot is moving on a horizontal plane surface. Several experiments have been performed, in both virtual and real scenarios, to validate the designed trajectory-tracking controller, while the AATV negotiates rubble, stairs, and complex terrain surfaces. Results are compared with both the performance of an alternative control strategy and the ability of skilled human operators, manually controlling the actively articulated components of the robot. C 2015 Wiley Periodicals, Inc.

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