Online Gain Adaptation of Whole-Body Control for Legged Robots with Unknown Disturbances

This paper proposes an online gain adaptation approach to enhance the robustness of whole-body control (WBC) framework for legged robots under unknown external force disturbances. Without properly accounting for external forces, the closed-loop control system incorporating WBC may become unstable, and therefore the desired task goals may not be achievable. To study the effects of external disturbances, we analyze the behavior of our current WBC framework via the use of both full-body and centroidal dynamics. In turn, we propose a way to adapt feedback gains for stabilizing the controlled system automatically. Based on model approximations and stability theory, we propose three conditions to ensure that the adjusted gains are suitable for stabilizing a robot under WBC. The proposed approach has four contributions. We make it possible to estimate the unknown disturbances without force/torque sensors. We then compute adaptive gains based on theoretic stability analysis incorporating the unknown forces at the joint actuation level. We demonstrate that the proposed method reduces task tracking errors under the effect of external forces on the robot. In addition, the proposed method is easy-to-use without further modifications of the controllers and task specifications. The resulting gain adaptation process is able to run in real-time. Finally, we verify the effectiveness of our method both in simulations and experiments using the bipedal robot Draco2 and the humanoid robot Valkyrie.

A new robust control strategy for axial flux permanent magnet motor applied on legged lunar robots

Legged robots have the advantage of strong terrain adaptability in lunar exploration. A new robust controller is designed for axial flux permanent magnet motors applied on the legged lunar robots to diminish the disturbance from uncertainty and external circumstance. The theoretical verification is carried out through Lyapunov stability theory. The numerical simulation and real-time experiment are carried out to access the stability and dynamic property of the systems adopting the proposed controller. The results are compared with the traditional control strategies to demonstrate the advantages of the proposed controller. The new robust controller contributes to the dynamic stability of legged lunar robots and is also appropriate for the similar mechanical systems.

A new bionic hydraulic actuator system for legged robots with impact buffering, impact energy absorption, impact energy storage, and force burst

It is a big challenge for bionic legged robots to realize desired jumping heights and forward-running speeds, let alone achieve springbok-style jump-running. A key limitation is that there is no actuator system that can mimic the springbok’s muscle system to drive leg–foot system movements. In this paper, we analyze the movement process of springboks and summarize some key characteristics of actuator systems. Some key concepts are then identified based on these key characteristics. Next, we propose a new bionic hydraulic joint actuator system with impact buffering, impact energy absorption, impact energy storage, and force burst, which can be applied to various legged robots to achieve higher running speeds, higher jumping heights, longer endurance, heavier loads, and lighter mass.

Learning Neuroplastic Matching of Robot Dynamics in Closed-loop CPGs

Legged robots have the potential to show locomotion performance with reduced control effort and energy efficiency by leveraging elastic structures inspired by animals' elastic tendons and muscles. However, it remains a challenge to match the natural dynamics of complex legged robots and their control task dynamics. Here we present a framework to match control task dynamics and natural dynamics based on the neuroelasticity and neuroplasticity concept. Inspired by animals we design quadruped robot Morti with strong natural dynamics as a testing platform. It is controlled through a bioinspired closed-loop central pattern generator (CPG) that is designed to neuroelastically mitigate short term perturbations using sparse contact feedback. We use the amount of neuroelastic activity as a proxy to quantify the dynamics' mismatching. By minimizing neuroelastic activity, we neuroplastically match the control task dynamics to the robot's natural dynamics. Through matching the robot learns to walk within one hour with only sparse feedback and improves its energy efficiency without explicitly minimizing it in the cost function.

Robots with Tails

Until recently, most four-legged robots have lacked a feature that is found again and again in nature—a tail. Studies of animal locomotion and robots in the laboratory indicate that leaving out tails has been a design drawback. In fact, research conducted by our lab at Virginia Tech has shown that an articulated robotic tail can effectively maneuver and stabilize a quadruped both for static and dynamic locomotion.

Large-scale Network Survivability Mathematical Association Model under Set Pair Analysis Theory

With the expansion of the application field of robots, the use of eight-legged bionic robots to assist or replace human operations in various complex and extreme terrains is constantly being explored. This paper uses octopus as a bionic object, designs an eight-eccentric wheel walking platform, and studies its dynamics, kinematics and trajectory planning. This paper first investigates the development history and research status of multi-legged robots in many countries, analyzes the shortcomings of octa-legged robots, and proposes improved solutions on this basis. Through the bionic of the octopus structure, the Catia software is used to design and establish a three-dimensional model of the octopus-like eight-eccentric wheel robot. By importing the three-dimensional model into the dynamic analysis software Adams for simulation, after adding constraints, driving, torque and contact force, the various functions of the platform are simulated to obtain linear wheel walking, rotary motion, linear leg walking, the parameters of jumping motion and obstacle-crossing motion are drawn into tables for intuitive analysis, and virtual prototype simulation is used to verify the correctness of the established model and trajectory planning. The research in this paper lays a theoretical foundation for the development and application of this eight-eccentric wheel bionic robot.

Modeling and base parameters identification of legged robots

This paper first uses a decoupling modeling method to model legged robots. The method groups all the degrees of freedom according to the number of limbs, regarding each limb as a manipulator with serial structure, which greatly reduces the number of dynamic parameters that need to be identified simultaneously. On this basis, a step-by-step identification method from the end-effector link to the base link, referred to as “E-B” identification method, is proposed. Simulation verification is carried out on a quadruped robot with 16 degrees of freedom in Gazebo, and the validity of the method proposed is discussed.