Maneuverability in Dynamic Vertical Climbing

Brown, Jason; Austin, Max P.; Kanwar, Bharat; Jonas, Tyler E.; Clark, Jonathan E.

doi:10.1109/iros.2018.8594074

Cited by 5 publications

(8 citation statements)

References 13 publications

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“…For example, birds and insects have claws and hairs on their feet to increase the chance of mechanical interlocks with rough surfaces, which have been studied by roboticists. [25,[29][30][31][32][33] The hardness of a target surface is another important factor in interlocking through penetration. Regardless of the surface's roughness, a sharp end-tip can penetrate the soft surface to make an engagement.…”

Section: Engagement Mechanismmentioning

confidence: 99%

Avian‐Inspired Perching Mechanism for Jumping Robots

Kim

Woodward

Sitti

2023

Advanced Intelligent Systems

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The integration of multiple motion strategies in robots has been actively studied to expand the working environment through the addition of new locomotion modes, such as aquatic (swimming), terrestrial (walking and rolling), and aerial (flying and perching). The focus has been on the development of the mechanisms necessary to integrate multimodal locomotion capability. For example, four leg mechanisms connected with a membrane allow for the integration of gliding and walking; [1] a transformable wing mechanism integrates flying and walking [2] ; single-actuated leg mechanisms integrate amphibious walking motions on the water surface and solid terrain; [3] a bio-inspired, [4,5] wheel-like propeller, [6] and leg-flipper [7] mechanisms integrate swimming and walking. These adaptations allow the robot to interact with the environment in new ways, creating the new locomotion modes.Furthermore, from varying the working environment, roboticists have also studied strategic interactions between integrated locomotion modes. Each mode can cooperate to complement each other, maximizing performance of the integrated modes. In the case of integrated jumping and gliding modes, jumping mode provides the potential energy for gliding. The integrated gliding transforms the potential energy into propulsion using aerodynamics and generates longer jumping distances than a single jump. [8][9][10][11][12] Integrated walking and flying modes can also be very complimentary as orientation control is one of the challenging points for the bipedal walking robots. The actuators for flight control can assist in orientation control for the walking mode. [13] In addition, during near surface flight, intermittent surface contact can be used to stabilize the robot under external disturbances, such as air flows.The integration of perching into jumping robots can both expand the working environment and provide a complimentary behavior to enhance the jumping locomotion itself, allowing for greater jump height, longer jump distance, or more variability in jumping direction in general. Furthermore, jumping-gliding robots can maximize the gliding distance by integrating a perching motion to allow for gliding from the greater height and velocity achievable by jumping from a perch. In addition to locomotion-specific performance gains, perching provides task-specific benefits, such as exploring a wider area from an elevated position without power usage, [14,15] and charging batteries on the perched surface. [16] However, both perching and jumping from the perch have yet to be explored.This work develops an avian-inspired perching mechanism to integrate perching with a jumping robot, as seen in Figure 1A. The perching mechanism is designed to absorb the perching impact and establish an engagement with the surface while minimizing weight, as this is a key parameter in determining the jumping performance. Various works have developed shock-absorbing mechanisms: hydraulic compression [17] and viscoelastic material [18][19][20] and engagement types: grasping, [2...

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Section: Engagement Mechanismmentioning

confidence: 99%

Avian‐Inspired Perching Mechanism for Jumping Robots

Kim

Woodward

Sitti

2023

Advanced Intelligent Systems

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“…This study proposes to re-plan CoM motion via trajectory optimization to address the above limitations. Generating the proper CoM motion plays a critical role in vertical climbing Brown et al (2018), though most studies achieve it via biologically inspired motion pattern. Trajectory optimization with centroidal dynamics is becoming popular in locomotion community Orin et al (2013); Kim et al (2019); Carpentier and Mansard (2018); Dai et al (2014) due to its availability to handle friction condition simpler than solving full-body dynamics.…”

Section: Centroidal Trajectory Optimizationmentioning

confidence: 99%

“…Most current studies on climbing robots focused on their design and mechanism and only a few studies have been conducted on dynamic robot climbing behavior. Several studies propose to utilize biologically inspired templates to generate climbing motions Brown et al (2018) , Lynch et al (2012) , but their implementations are limited to certain behavior and do not consider any constraint regarding safe holdings that should be guaranteed for stable climbing. Motion planning and control have also been studied for free-climbing Bretl (2006) ; Miller and Rock (2008) and vertical wall climbing Lin et al (2019) ; Lin et al (2018) .…”

Section: Introductionmentioning

confidence: 99%

Adaptive robot climbing with magnetic feet in unknown slippery structure

2022

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Firm foot contact is the top priority of climbing robots to avoid catastrophic events, especially when working at height. This study proposes a robust planning and control framework for climbing robots that provides robustness to slippage in unknown environments. The framework includes 1) a center of mass (CoM) trajectory optimization under the estimated contact condition, 2) Kalman filter–like approach for uncertain environment parameter estimation and subsequent CoM trajectory re-planing, and 3) an online weight adaptation approach for whole-body control (WBC) framework that can adjust the ground reaction force (GRF) distribution in real time. Though the friction and adhesion characteristics are often assumed to be known, the presence of several factors that lead to a reduction in adhesion may cause critical problems for climbing robots. To address this issue safely and effectively, this study suggests estimating unknown contact parameters in real time and using the evaluated contact information to optimize climbing motion. Since slippage is a crucial behavior and requires instant recovery, the computation time for motion re-planning is also critical. The proposed CoM trajectory optimization algorithm achieved state-of-art fast computation via trajectory parameterization with several reasonable assumptions and linear algebra tricks. Last, an online weight adaptation approach is presented in the study to stabilize slippery motions within the WBC framework. This can help a robot to manage the slippage at the very last control step by redistributing the desired GRF. In order to verify the effectiveness of our method, we have tested our algorithm and provided benchmarks in simulation using a magnetic-legged climbing robot Manegto.

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“…By observation of the running, swimming, and climbing behaviors of sprawled posture animals (like geckos and beetles), similarities in the center of mass (COM) patterns (such as those captured by these bipedal models) seem apparent (figure 2). Moreover, fast robots such as TAILS [29] and BOB [32] (figures 2(B) and (C) respectively) have shown a high degree of accuracy with instantiating these model dynamics. It is for these reasons that this model of swimming is explored in the lateral plane.…”

Section: Modelmentioning

confidence: 99%

“…Parameter variation studies of this model are used to investigate its general behaviors when swimming (sections 4 and 5). Section 6 describes how, based on these results, a multi-modal robot called AquaClimber (figures 1(A) and (B)) is developed using a morphology similar to the gecko-inspired (figure 2(A)) BOB (Bipedal Oscillating roBot) family of climbing robots [27][28][29] (figures 2(B) and (C)). Experimental studies (compared with simulations) regarding frequency, hand shape, and arm compliance are described section 7 with the results presented in section 8 Experimental Results.…”

Section: Introductionmentioning

confidence: 99%

AquaClimber: a limbed swimming and climbing robot based on reduced order models

Austin¹,

Chase²,

Stratum³

et al. 2022

Bioinspir. Biomim.

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Many legged robots have taken insight from animals to run, jump, and climb. Very few, however, have extended the ﬂexibility of limbs to the task of swimming. In this paper, we address the study of multi-modal limbed locomotion by extending our lateral plane reduced order dynamic model of climbing to swimming. Following this, we develop a robot, AquaClimber, which utilizes the model’s locomotive style, similar to human freestyle swimming, to propel itself through ﬂuid and to climb vertical walls, as well as transition between the two. A comparison of simulation and model results indicate that the simulation can predict how hand design, arm compliance, and driving frequency affect swimming speed and behavior. Using this reduced order model, we have successfully developed the ﬁrst limbed aquaticscansorial multi-modal robot.

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Maneuverability in Dynamic Vertical Climbing

Cited by 5 publications

References 13 publications

Avian‐Inspired Perching Mechanism for Jumping Robots

Avian‐Inspired Perching Mechanism for Jumping Robots

Adaptive robot climbing with magnetic feet in unknown slippery structure

AquaClimber: a limbed swimming and climbing robot based on reduced order models

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