Footstep Planning for Autonomous Walking Over Rough Terrain

Robert, J Griffin; Wiedebach, Georg; McCrory, Stephen; Sylvain, Bertrand; In-Ho, Lee; Jerry, Pratt

doi:10.48550/arxiv.1907.08673

Cited by 3 publications

(6 citation statements)

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“…[32], and a novel state-action modeling approach. In addition to current footstep planners as in [6] [22][25] [30][32], our approach does not rely on cyclic gaits and allows finding a suitable floating base pose for each foothold configuration and vice-versa, providing better initialization for trajectory optimization.…”

Section: A Contributionsmentioning

confidence: 99%

“…A suitably chosen action set can easily bypass the equilibrium feasibility problem but may not take into account the robot's full locomotion capabilities. Search-based footstep planning has a rich history of publications [28][29] [30] but few deal with uneven flat surfaces [31] or rough terrain [6] [32]. In this work, we even demonstrate a solver for irregular terrain tasks that includes curved and even non-contiguous contacts (see Fig.…”

Section: Introductionmentioning

confidence: 95%

“…In the last decade, the locomotion capabilities of legged robots have improved significantly and now offer the potential for first real-world applications. New Whole-Body Control (WBC) approaches for bipedal robots [1][2][3] [4] have been applied to capable robots such as Boston Dynamics' Atlas or NASA's Valkyrie [5] and demonstrated exceptional capabilities in traversing terrain [6] up to walking on edges with partial footholds [7].…”

Section: Introductionmentioning

confidence: 99%

“…A footstep planner is often strongly tied to a specific robot platform or at least to the basic kinematic structure, such as for bipeds [6][30] [33] or for quadrupeds [22]. Our preceding modular and reusable approach also applies only for bipedal robots [32].…”

Section: Introductionmentioning

confidence: 99%

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A Universal Footstep Planning Methodology for Continuous Walking in Challenging Terrain Applicable to Different Types of Legged Robots

Stumpf,

von Stryk

2022

2022 International Conference on Robotics and Automation (ICRA)

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In recent years, the capabilities of legged locomotion controllers have been significantly advanced enabling them to traverse basic types of uneven terrain without visual perception. However, safely and autonomously traversing longer distances over difficult uneven terrain requires appropriate motion planning using online collected environmental knowledge. In this paper, we present such a novel methodology for generic closed-loop preceding horizon footstep planning that enables legged robots equipped with capable locomotion controllers to autonomously traverse previously unknown terrain while continuously walking long distances. Hereby, our approach addresses the challenge of online terrain perception and soft real-time footstep planning. The proposed new formulation of the search-based planning problem makes no specific assumptions about the robot kinematics (e.g. number of legs) or the used locomotion control schemes. Therefore, it can be applied to a broad range of different types of legged robots. Unlike current methods, the proposed new framework can optionally consider the floating base as part of the state-space. It is possible to configure the complexity of the planner online, from efficiently solving tasks in flat terrain to using non-contiguous contacts in highly challenging terrain. Finally, the presented methodology is successfully applied and evaluated in virtual and real experiments on state of the art bipedal, quadrupedal, and a novel eight-legged robot.

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Section: A Contributionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Universal Footstep Planning Methodology for Continuous Walking in Challenging Terrain Applicable to Different Types of Legged Robots

Stumpf,

von Stryk

2022

2022 International Conference on Robotics and Automation (ICRA)

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“…Footstep planning are generally based on graph search algorithm with a rich history [11], [10]. In our target framework, the footstep planning is composed of two stages: (i) generating a collision-free 2D body path; (ii) planning the footsteps based on the generated path.…”

Section: A A* Footstep Planningmentioning

confidence: 99%

A Robust Model-Based Biped Locomotion Framework Based on Three-Mass Model: From Planning to Control

Kasaei

Ahmadi

Lau

et al. 2020

2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

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Biped robots are inherently unstable because of their complex kinematics as well as dynamics. Despite types of research in developing biped locomotion, the performance of biped locomotion is still far from the expectations.This paper proposes a model-based framework to generate stable biped locomotion. The core of this framework is an abstract dynamics model which is composed of three masses to consider the dynamics of stance leg, torso and swing leg for minimizing the tracking problems. According to this dynamics model, we propose a modular walking reference trajectories planner which takes into account obstacles to plan all the references. Moreover, this dynamics model is used to formulate the low-level controller as a Model Predictive Control (MPC) scheme which can consider some constraints in the states of the system, inputs, outputs and also mixed input-output.The performance and the robustness of the proposed framework are validated by performing several simulations using MATLAB. The simulation results show that the proposed framework is capable of generating the biped locomotion robustly.

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Neuro-Cognitive Locomotion with Dynamic Attention on Topological Structure

2023

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This paper discusses a mechanism for integrating locomotion with cognition in robots. We demonstrate an attentional ability model that can dynamically change the focus of its perceptual area by integrating attention and perception to generate behavior. The proposed model considers both internal sensory information and also external sensory information. We also propose affordance detection that identifies different actions depending on the robot’s immediate possibilities. Attention is represented in a topological structure generated by a growing neural gas that uses 3D point-cloud data. When the robot faces an obstacle, the topological map density increases in the suspected obstacle area. From here, affordance information is processed directly into the behavior pattern generator, which comprises interconnections between motor and internal sensory neurons. The attention model increases the density associated with the suspected obstacle to produce a detailed representation of the obstacle. Then, the robot processes the cognitive information to enact a short-term adaptation to its locomotion by changing its swing pattern or movement plan. To test the effectiveness of the proposed model, it is implemented in a computer simulation and also in a medium-sized, four-legged robot. The experiments validate the advantages in three categories: (1) Development of attention model using topological structure, (2) Integration between attention and affordance in moving behavior, (3) Integration of exteroceptive sensory information to lower-level control of locomotion generator.

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Footstep Planning for Autonomous Walking Over Rough Terrain

Cited by 3 publications

References 0 publications

A Universal Footstep Planning Methodology for Continuous Walking in Challenging Terrain Applicable to Different Types of Legged Robots

A Universal Footstep Planning Methodology for Continuous Walking in Challenging Terrain Applicable to Different Types of Legged Robots

A Robust Model-Based Biped Locomotion Framework Based on Three-Mass Model: From Planning to Control

Neuro-Cognitive Locomotion with Dynamic Attention on Topological Structure

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