Autonomous legged hill ascent

Ilhan, B. Deniz; Johnson, Aaron M.; Koditschek, Daniel E.

doi:10.1002/rob.21779

Cited by 22 publications

(31 citation statements)

References 81 publications

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“…These are sufficient to recruit the desired interaction between the body morphology and the environment structure, and the robot's heading stabilizes in absence of any body-level sensing (AEI). Ilhan et al (2018) develop a controller that drives a robot toward the locally most elevated position from any start location in a gentle hillslope environment punctured by tree-like, disk-shaped obstacles (EM). They test their controller on a physical sixlegged robot walking on unstructured, forested hillslopes, using the top of the hillslope as the goal location.…”

Section: Characterizing Interactions With Obstaclesmentioning

confidence: 99%

Examples of Gibsonian Affordances in Legged Robotics Research Using an Empirical, Generative Framework

2020

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Evidence from empirical literature suggests that explainable complex behaviors can be built from structured compositions of explainable component behaviors with known properties. Such component behaviors can be built to directly perceive and exploit affordances. Using six examples of recent research in legged robot locomotion, we suggest that robots can be programmed to effectively exploit affordances without developing explicit internal models of them. We use a generative framework to discuss the examples, because it helps us to separate-and thus clarify the relationship between-description of affordance exploitation from description of the internal representations used by the robot in that exploitation. Under this framework, details of the architecture and environment are related to the emergent behavior of the system via a generative explanation. For example, the specific method of information processing a robot uses might be related to the affordance the robot is designed to exploit via a formal analysis of its control policy. By considering the mutuality of the agent-environment system during robot behavior design, roboticists can thus develop robust architectures which implicitly exploit affordances. The manner of this exploitation is made explicit by a well constructed generative explanation.

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Section: Characterizing Interactions With Obstaclesmentioning

confidence: 99%

Examples of Gibsonian Affordances in Legged Robotics Research Using an Empirical, Generative Framework

2020

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“…To characterize the spatial variation of erodibility in situ, we mounted the direct-drive robotic leg on a mobile ground-based platform, the RHex robot (Saranli et al, 2001a; Figure 2a). RHex is a bio-inspired, hexapedal robot that exhibits high mobility over a variety of outdoor environments, including terrain with obstacles (Saranli et al, 2001b), inclinations from hills (Ilhan et al, 2018) and stairs (Johnson et al, 2011), and desert dunes (Roberts, Duperret, Johnson, et al, 2014;Roberts, Duperret, Li, et al, 2014;Qian et al, 2017). The RHex robot has been employed for various aeolian research expeditions (Roberts, Duperret, Johnson, et al, 2014;Roberts, Duperret, Li, et al, 2014;Qian et al, 2017;Qian, Lancaster, 2016;Qian, Lee, 2016;Van Pelt et al, 2016) and has demonstrated its capability to perform a wide variety of measurements including wind speed, saltation grain counts, and erodibility in strong wind conditions to obtain high spatiotemporal resolution field data sets (Qian et al, 2017).…”

Section: Plowing Field Experimentsmentioning

confidence: 99%

Rapid In Situ Characterization of Soil Erodibility With a Field Deployable Robot

et al. 2019

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Predicting the susceptibility of soil to wind erosion is difficult because it is a multivariate function of grain size, soil moisture, compaction, and biological growth. Erosive agents like plowing and grazing also differ in mechanism from entrainment by fluid shear; it is unclear if and how erosion thresholds for each process are related. Here we demonstrate the potential to rapidly assemble empirical maps of erodibility while also examining what controls it, using a novel “plowing” test of surface‐soil shear resistance (τr) performed by a semi‐autonomous robot. Field work at White Sands National Monument, New Mexico, United States, examined gradients in erodibility at two scales: (i) soil moisture changes from dry dune crest to wet interdune (tens of meters) and (ii) downwind‐increasing dune stabilization associated with growth of plants and salt and biological crusts (kilometers). We found that soil moisture changes of a few percent corresponded to a doubling of τr, a result confirmed by laboratory experiments, and that soil crusts conferred stability that was comparable to moisture effects. We then compared different mechanisms of mechanical perturbation in a controlled laboratory setting. A new “kick‐out” test determines peak shear resistance of the surface soil as a proxy for yield strength. Kick‐out resistance exhibited a relation with soil moisture that was distinct from the plowing test and that was correlated with the independently measured threshold‐fluid stress for wind erosion. Results show that our new method maps soil erodibility in arid environments and provides an understanding of environmental controls on variations in soil erodibility.

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“…The addition of a gearbox would reduce actuator transparency [7] and make the robot unable to act as a force sensor; the foot size can be increased by about a factor of two, but too large a foot and the inertia will again render the force sensor useless; and stiffening the legs comes at a high cost from the battery, since the spring force is virtual rather than mechanical. The increase in gearbox ratio has also slowed X-RHex down significantly: whereas a standard X-RHex can keep up with a jogging or running human on rugged terrain [8], the highly geared desert version has a top speed at best closer to human walking speed [5].…”

Section: A the Ghost Minitaur Robot Can Be Used To Measure Ground Ermentioning

confidence: 99%

Reactive velocity control reduces energetic cost of jumping with a virtual leg spring on simulated granular media

Roberts

Koditschek²

2018

2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Robots capable of dynamic locomotion behaviors and high-bandwidth sensing with their limbs have a high cost of transport, especially when locomoting over highly dissipative substrates such as sand. We formulate the problem of reducing the energetic cost of locomotion by a Minitaur robot on sand, reacting to robot state variables in the inertial world frame without modeling the ground online. Using a bulkbehavior model of high-velocity intrusions into dry granular media, we simulated single jumps by a onelegged hopper using a Raibert-style compression-extension virtual leg spring. We compose this controller with a controller that added damping to the leg spring in proportion to the intrusion velocity of the robot's foot into the simulated sand while the robot is pushing off in the second half of stance. This has the effect of both reducing the torque exerted by the motors because the added virtual "active damping" force acts in opposition to the virtual leg spring force, and reducing the transfer of energy from the robot to the sand by slowing the intrusion velocity of the foot. Varying the simulated robot's initial conditions and the simulated ground parameters, we gained a consistent 20% energy savings by adding active damping with no cost in apex height. For more information, see the Kod*lab website: kodlab.seas.upenn.edu

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Autonomous legged hill ascent

Cited by 22 publications

References 81 publications

Examples of Gibsonian Affordances in Legged Robotics Research Using an Empirical, Generative Framework

Examples of Gibsonian Affordances in Legged Robotics Research Using an Empirical, Generative Framework

Rapid In Situ Characterization of Soil Erodibility With a Field Deployable Robot

Reactive velocity control reduces energetic cost of jumping with a virtual leg spring on simulated granular media

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