Running over unknown rough terrain with a one-legged planar robot

Andrews, Ben; Miller, Bruce D.; Schmitt, John; Clark, Jonathan E.

doi:10.1088/1748-3182/6/2/026009

Cited by 56 publications

(47 citation statements)

References 28 publications

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“…Real world locomotion on the other hand has to deal with uneven terrain causing energetic perturbations. On this, recently Andrews et al (2011) suggested to adjust SLIP-dynamics. They successfully implemented a control scheme ("active energy removal") in simulation and hardware, which varied the "force-free leg length" (rest length of the spring).…”

Section: Discussionmentioning

confidence: 99%

Energy management that generates terrain following versus apex-preserving hopping in man and machine

et al. 2012

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While hopping, 12 subjects experienced a sudden step down of 5 or 10 cm. Results revealed that the hopping style was "terrain following". It means that the subjects pursued to keep the distance between maximum hopping height (apex) and ground profile constant. The spring-loaded inverse pendulum (SLIP) model, however, which is currently considered as template for stable legged locomotion would predict apex-preserving hopping, by which the absolute maximal hopping height is kept constant regardless of changes of the ground level. To get more insight into the physics of hopping, we outlined two concepts of energy management: "constant energy supply", by which in each bounce--regardless of perturbations--the same amount of mechanical energy is injected, and "lost energy supply", by which the mechanical energy that is going to be dissipated in the current cycle is assessed and replenished. When tested by simulations and on a robot testbed capable of hopping, constant energy supply generated stable and robust terrain following hopping, whereas lost energy supply led to something like apex-preserving hopping, which, however, lacks stability as well as robustness. Comparing simulated and machine hopping with human hopping suggests that constant energy supply has a good chance to be used by humans to generate hopping.

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Section: Discussionmentioning

confidence: 99%

Energy management that generates terrain following versus apex-preserving hopping in man and machine

et al. 2012

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“…Alternative dynamic templates that include actuation have been proposed (Schmitt and Clark, 2009;Seipel and Holmes, 2007), but little experimental evidence exists to support one alternative template over another. Discovery of dynamic templates for unsteady locomotion would provide insights into mechanisms for robust stability in varied terrain, and could inspire novel control methods and mechanical designs for prosthetics and legged robots (Andrews et al, 2011;Grizzle et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Birds achieve high robustness in uneven terrain through active control of landing conditions

Birn-Jeffery

Daley

2012

Journal of Experimental Biology

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SUMMARYWe understand little about how animals adjust locomotor behaviour to negotiate uneven terrain. The mechanical demands and constraints of such behaviours likely differ from uniform terrain locomotion. Here we investigated how common pheasants negotiate visible obstacles with heights from 10 to 50% of leg length. Our goal was to determine the neuro-mechanical strategies used to achieve robust stability, and address whether strategies vary with obstacle height. We found that control of landing conditions was crucial for minimising fluctuations in stance leg loading and work in uneven terrain. Variation in touchdown leg angle ( TD ) was correlated with the orientation of ground force during stance, and the angle between the leg and body velocity vector at touchdown ( TD ) was correlated with net limb work. Pheasants actively targeted obstacles to control body velocity and leg posture at touchdown to achieve nearly steady dynamics on the obstacle step. In the approach step to an obstacle, the birds produced net positive limb work to launch themselves upward. On the obstacle, body dynamics were similar to uniform terrain. Pheasants also increased swing leg retraction velocity during obstacle negotiation, which we suggest is an active strategy to minimise fluctuations in peak force and leg posture in uneven terrain. Thus, pheasants appear to achieve robustly stable locomotion through a combination of path planning using visual feedback and active adjustment of leg swing dynamics to control landing conditions. We suggest that strategies for robust stability are context specific, depending on the quality of sensory feedback available, especially visual input.

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“…In this case, a stance phase control would be required to bring the robot back to the preferred forward speed, or the robot would continue with a higher horizontal velocity. A simple and bio-inspired stance phase technique that was proposed by Schmitt et al [36] and investigated more by [37] and [38] could be used to dissipate the gained energy. Since the energy that requires dissipation is only that due to the drop perturbation, the cost of dissipating this energy in subsequent steps is the same across all control policies compared.…”

Section: Discussionmentioning

confidence: 99%

Bio-inspired swing leg control for spring-mass robots running on ground with unexpected height disturbance

et al. 2013

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Abstract.We proposed three swing leg control policies for spring-mass running robots, inspired by experimental data from our recent collaborative work on ground running birds. Previous investigations suggest that animals may prioritize injury avoidance and/or efficiency as their objective function during running rather than maintaining limit-cycle stability. Therefore, in this study we targeted structural capacity (maximum leg force to avoid damage) and efficiency as the main goals for our control policies, since these objective functions are crucial to reduce motor size and structure weight. Each proposed policy controls the leg angle as a function of time during flight phase such that its objective function during the subsequent stance phase is regulated. The three objective functions that are regulated in the control policies are i) the leg peak force, ii) the axial impulse, and iii) the leg actuator work. It should be noted that each control policy regulates one single objective function. Surprisingly, all three swing leg control policies result in nearly identical subsequent stance phase dynamics. This implies that the implementation of any of the proposed control policies would satisfy both goals (damage avoidance and efficiency) at once. Furthermore, all three control policies require a surprisingly simple leg angle adjustment: leg retraction with constant angular acceleration.

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Running over unknown rough terrain with a one-legged planar robot

Cited by 56 publications

References 28 publications

Energy management that generates terrain following versus apex-preserving hopping in man and machine

Energy management that generates terrain following versus apex-preserving hopping in man and machine

Birds achieve high robustness in uneven terrain through active control of landing conditions

Bio-inspired swing leg control for spring-mass robots running on ground with unexpected height disturbance

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