3D dynamic walking on stepping stones with control barrier functions

Nguyen, Quan; Hereid, Ayonga; Grizzle, Jessy W.; Ames, Aaron D.; Sreenath, Koushil

doi:10.1109/cdc.2016.7798370

Cited by 105 publications

(81 citation statements)

References 16 publications

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“…We hope to facilitate this by integrating the discrete-time CBF controller presented here with the continuous-time controllers presented in [22,25,24,26].…”

Section: Discussionmentioning

confidence: 99%

“…In this paper, we look at the discrete-time version of the CBF-CLF based control developed in [2] as the Poincaré map based control problem for path-following and obstacle avoidance for a bipedal robot is inherently discrete-time due to the stride-to-stride event-based control action. Moreover, continuous-time controllers presented in [23,22] only allow for within-stride control of the foot position and cannot be applied directly to this problem. Remark 12.…”

Section: E Obstacle Avoidancementioning

confidence: 99%

“…The discrete time CBF-CLF controller (30) can be concatenated with a continuous-time CBF-CLF controller [9,22,26] to traverse over more complex terrains such as stepping stones while avoiding obstacles.…”

Section: E Obstacle Avoidancementioning

confidence: 99%

“…In the context of limit-cycle walkers, footstep placement strategies based on barrier functions to traverse terrains with discrete footholds is presented in [22,24,26] for 2D robots and in [23] for high degree of freedom 3D robots. Navigation planning of 3D dynamic walkers has been studied in [11] and more recently in [21] by composing asymptotically stable motion primitives.…”

Section: Introductionmentioning

confidence: 99%

“…Barrier function based control techniques have recently gained success in a wide variety continuous-time systems for safety-critical applications such as precise footstep placement of high degree of freedom bipedal robots [23,22,24,26,27], adaptive cruise control systems [2], multi-agent systems [30,4], and quadrotor systems [33,34,32]. In these, the problem of stabilization with guaranteed safety is posed as a constrained convex optimization problem, that combines control Lyapunov and control barrier functions, and solves for an optimal control input that maintains the states of the system with a predefined safety set.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Discrete Control Barrier Functions for Safety-Critical Control of Discrete Systems with Application to Bipedal Robot Navigation

Agrawal

Sreenath

2017

Robotics: Science and Systems XIII

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189

158

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Abstract-In this paper, we extend the concept of control barrier functions, developed initially for continuous time systems, to the discrete-time domain. We demonstrate safety-critical control for nonlinear discrete-time systems with applications to 3D bipedal robot navigation. Particularly, we mathematically analyze two different formulations of control barrier functions, based on their continuous-time counterparts, and demonstrate how these can be applied to discrete-time systems. We show that the resulting formulation is a nonlinear program in contrast to the quadratic program for continuous-time systems and under certain conditions, the nonlinear program can be formulated as a quadratically constrained quadratic program. Furthermore, using the developed concept of discrete control barrier functions, we present a novel control method to address the problem of navigation of a high-dimensional bipedal robot through environments with moving obstacles that present time-varying safety-critical constraints.

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“…We hope to facilitate this by integrating the discrete-time CBF controller presented here with the continuous-time controllers presented in [22,25,24,26].…”

Section: Discussionmentioning

confidence: 99%

Section: E Obstacle Avoidancementioning

confidence: 99%

Section: E Obstacle Avoidancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Discrete Control Barrier Functions for Safety-Critical Control of Discrete Systems with Application to Bipedal Robot Navigation

Agrawal

Sreenath

2017

Robotics: Science and Systems XIII

Self Cite

189

158

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show abstract

Dynamical system learning using extreme learning machines with safety and stability guarantees

Salehi

Rotithor

Yao

et al. 2021

Adaptive Control & Signal

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Summary This article presents a continuous dynamical system model learning methodology that can be used to generate reference trajectories for the autonomous systems to follow, such that these trajectories are invariant to a given closed set and uniformly ultimately bounded with respect to an equilibrium point inside the closed set. The autonomous system dynamics are approximated using extreme learning machines (ELM), the parameters of which are learned subject to the safety constraints expressed using a reciprocal barrier function, and the stability constraints derived using a Lyapunov analysis in the presence of the ELM reconstruction error. This formulation leads to solving a constrained quadratic program (QP) that includes a finite number of decision variables with an infinite number of constraints. Theorems are developed to relax the QP with infinite number of constraints to a QP with a finite number of constraints which can be practically implemented using a QP solver. In addition, an active sampling methodology is developed that further reduced the number of required constraints for the QP by only evaluating the constraints at a smaller subset of points. The proposed method is validated using a motion reproduction task on a seven degree‐of‐freedom Baxter robot, where the task space position and velocity dynamics are learned using the presented methodology.

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Dynamic Walking on Stepping Stones with Gait Library and Control Barrier Functions

Nguyen

Grizzle

et al. 2020

Springer Proceedings in Advanced Robotics

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3D dynamic walking on stepping stones with control barrier functions

Cited by 105 publications

References 16 publications

Discrete Control Barrier Functions for Safety-Critical Control of Discrete Systems with Application to Bipedal Robot Navigation

Discrete Control Barrier Functions for Safety-Critical Control of Discrete Systems with Application to Bipedal Robot Navigation

Dynamical system learning using extreme learning machines with safety and stability guarantees

Dynamic Walking on Stepping Stones with Gait Library and Control Barrier Functions

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