Compliant Control of Quadruped Robots for Assistive Load Carrying

2025-03-13

AI Summary

Quadruped robots employed in assisted load-carrying suffer from acceleration instability, degraded body stability, and heightened collision risk with forward collaborative agents due to dynamic payload variations. Method: This paper proposes a real-time quadratic programming (QP) optimization framework integrating onboard-sensor-based joint torque estimation, admittance control, and Control Barrier Function (CBF)-enforced safety constraints. Contribution/Results: To the best of our knowledge, this is the first work to introduce CBF-guaranteed admittance control for quadrupedal load-carrying—enabling robust disturbance rejection, precise acceleration tracking across full payload ranges, and hard collision avoidance with forward agents. The method relies solely on embedded sensors, requires no external localization, and satisfies real-time embedded deployment constraints. Experimental validation on both physical hardware and high-fidelity simulation demonstrates significant improvements in load-carrying stability and human-robot collaborative safety, confirming its applicability to industrial material handling and disaster search-and-rescue missions.

Technology Category

Intelligent Robots: Motion and Path PlanningHumans and AI: Human-Aware Planning and Behavior PredictionNatural Language Processing: Safety and Robustness

Application Category

Responsible Web: Machine-in-the-loop, human agency and autonomyEconomics, Online Markets and Human Computation: LLM based quality controls for crowd workGraph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This paper presents a novel method for assistive load carrying using quadruped robots. The controller uses proprioceptive sensor data to estimate external base wrench, that is used for precise control of the robot's acceleration during payload transport. The acceleration is controlled using a combination of admittance control and Control Barrier Function (CBF) based quadratic program (QP). The proposed controller rejects disturbances and maintains consistent performance under varying load conditions. Additionally, the built-in CBF guarantees collision avoidance with the collaborative agent in front of the robot. The efficacy of the overall controller is shown by its implementation on the physical hardware as well as numerical simulations. The proposed control framework aims to enhance the quadruped robot's ability to perform assistive tasks in various scenarios, from industrial applications to search and rescue operations.

Problem

• Develops a control method for quadruped robots carrying assistive loads.
• Uses proprioceptive data and admittance control for precise acceleration management.
• Ensures collision avoidance and consistent performance under varying load conditions.

Innovation

• Proprioceptive sensor data for external wrench estimation
• Admittance control combined with CBF-based QP
• Built-in CBF ensures collision avoidance