Footstep Planning on Uneven Terrain with Mixed-Integer Convex Optimization

Deits, Robin; Tedrake, Russ

doi:10.21236/ada609276

Cited by 157 publications

(176 citation statements)

References 11 publications

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“…To diminish the influence of the substrate irregularities, ants may use specialized adhesive tarsal pads that secure foot attachment [22] and benefit from polypedalism, which improves passive recovery from impulsive disruptions [8,9,48]. With neuromechanical and robotic control research often focusing on accurate foot placement [49] or navigational planning [50], our findings highlight the potential for developing decentralized mechanisms for navigating uneven terrain. Further, we show that ants in the field seek out substrates that enable faster walking speeds.…”

Section: Discussionmentioning

confidence: 99%

Rough substrates constrain walking speed in ants through modulation of stride frequency and not stride length

Clifton¹,

Holway²,

Gravish³

2019

Preprint

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Natural terrain is rarely flat. Substrate irregularities challenge walking animals to maintain stability, yet we lack quantitative assessments of walking performance and limb kinematics on naturally rough ground. We measured how continually rough 3D-printed substrates influence walking performance of Argentine ants by measuring walking speeds of workers from lab colonies and by testing colony-wide substrate preference in field experiments. Tracking limb motion in over 8,000 videos, we used statistical models that associate walking speed with limb kinematic parameters to compare movement over flat versus rough ground. We found that rough substrates reduced preferred and peak walking speeds by up to 42% and that ants actively avoided rough terrain in the field. Observed speed reductions were modulated primarily by shifts in stride frequency and not stride length, a pattern consistent across flat and rough substrates. Modeling revealed that walking speeds on rough substrates were accurately predicted based on flat walking data for over 89% of strides. Those strides that were not well modeled primarily involved limb perturbations, including missteps, active foot repositioning, and slipping. Together these findings relate kinematic mechanisms underlying walking performance on rough terrain to ecologically-relevant measures under field conditions.

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Section: Discussionmentioning

confidence: 99%

Rough substrates constrain walking speed in ants through modulation of stride frequency and not stride length

Clifton¹,

Holway²,

Gravish³

2019

Preprint

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“…Recently searching over continuous space rather than over a discrete graph has been gaining interest. One of the earlier works of actually fielded continuous space algorithms used a mixed integer quadratic program (MIQP) to compute footstep plans [7]. Like in [8], this approach requires a smart segmentation of the environment into convex regions in order to be tractable.…”

Section: Related Workmentioning

confidence: 99%

Footstep Planning for Autonomous Walking Over Rough Terrain

Griffin

Wiedebach

McCrory

et al. 2019

2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)

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To increase the speed of operation and reduce operator burden, humanoid robots must be able to function autonomously, even in complex, cluttered environments. For this to be possible, they must be able to quickly and efficiently compute desired footsteps to reach a goal. In this work, we present a new A* footstep planner that utilizes a planar region representation of the environment enable footstep planning over rough terrain. To increase the number of available footholds, we present an approach to allow the use of partial footholds during the planning process. The footstep plan solutions are then postprocessed to capture better solutions that lie between the lattice discretization of the footstep graph. We then demonstrate this planner over a variety of virtual and real world environments, including some that require partial footholds and rough terrain using the Atlas and Valkyrie humanoid robots.

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“…Exteroceptive-based perception (vision and range sensing) methods were developed during the DRC 2015, for footstep planning on flat uneven outdoors terrain. In [8], [26], a real-time optimization-based state estimation system was introduced for the ATLAS humanoids robot, where stereo fusion was used for planning locomotion on rough planar terrain, by extracting planar contact surfaces for navigation. In a different direction, a graph-based footstep planner was used in [27], [28], [29], using LiDAR/range environment data.…”

Section: Related Workmentioning

confidence: 99%

Curved patch mapping and tracking for irregular terrain modeling: Application to bipedal robot foot placement

Kanoulas

Tsagarakis

Vona

2019

Robotics and Autonomous Systems

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Legged robots need to make contact with irregular surfaces, when operating in unstructured natural terrains. Representing and perceiving these areas to reason about potential contact between a robot and its surrounding environment, is still largely an open problem. This paper introduces a new framework to model and map local rough terrain surfaces, for tasks such as bipedal robot foot placement. The system operates in real-time, on data from an RGB-D and an IMU sensor. We introduce a set of parametrized patch models and an algorithm to fit them in the environment. Potential contacts are identified as bounded curved patches of approximately the same size as the robot's foot sole. This includes sparse seed point sampling, point cloud neighborhood search, and patch fitting and validation. We also present a mapping and tracking system, where patches are maintained in a local spatial map around the robot as it moves. A bio-inspired sampling algorithm is introduced for finding salient contacts. We include a dense volumetric fusion layer for spatiotemporally tracking, using multiple depth data to reconstruct a local point cloud. We present experimental results on a mini-biped robot that performs foot placements on rocks, implementing a 3D foothold perception system, that uses the developed patch mapping and tracking framework.Index Terms-irregular surface modeling, foothold contact modeling, bounded curved patch modeling, curved patch fitting and tracking, 3D perception for bipedal robots, bipedal robot foot placement, rough terrain stepping, legged robot locomotion ! • Dimitrios Kanoulas and Nikos G. Tsagarakis are with the Humanoids and

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Footstep Planning on Uneven Terrain with Mixed-Integer Convex Optimization

Cited by 157 publications

References 11 publications

Rough substrates constrain walking speed in ants through modulation of stride frequency and not stride length

Rough substrates constrain walking speed in ants through modulation of stride frequency and not stride length

Footstep Planning for Autonomous Walking Over Rough Terrain

Curved patch mapping and tracking for irregular terrain modeling: Application to bipedal robot foot placement

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