A Friction-Driven Strategy for Agile Steering Wheel Manipulation by Humanoid Robots

Vehicle driving can substantially enhance the maneuverability of humanoid robots. Agile steering wheel manipulation requires rapid rotation in narrow spaces such as a cab, serving as the foundation for increasing driving speed, especially in an obstacle avoidance scenario. Generally, there are 3 human driving strategies, "Hand-to-Hand," "Hand-over-Hand," and "One-Hand." Based on the human driving motion data, we quantitatively analyze these strategies from 3 aspects, motion range of joint combination, motion region of the shoulder, and velocity of the manipulation. Then, a friction-driven manipulation strategy using one hand is proposed utilizing the similarity between a humanoid robot and a driver (human). It effectively addresses the requirements of both a small range of motion and rapid manipulation. To prevent the deformation of the steering wheel caused by excessive force, we construct an operating force model specifically for the steering wheel. This model accurately describes the relationship between the rotation resistance and the state of the steering wheel. In addition, we propose a quadratic programming (QP)-based control framework to servo the robot to track the end-effector position and target wrench output by this model. Finally, the effectiveness of this paper is evaluated through an obstacle avoidance scenario, achieving a maximum rotation velocity of 3.14 rad/s.

An Admittance Control Method Based on Parameters Fuzzification for Humanoid Steering Wheel Manipulation

Developing a human bionic manipulator to achieve certain humanoid behavioral skills is a rising problem. Enabling robots to operate the steering wheel to drive the vehicle is a challenging task. To address the problem, this work designs a novel 7-DOF (degree of freedom) humanoid manipulator based on the arm structure of human bionics. The 3-2-2 structural arrangement of the motors and the structural modifications at the wrist allow the manipulator to act more similar to a man. Meanwhile, to manipulate the steering wheel stably and compliantly, an admittance control approach is firstly applied for this case. Considering that the system parameters vary in configuration, we further introduce parameter fuzzification for admittance control. Designed simulations were carried out in Coppeliasim to verify the proposed control approach. As the result shows, the improved method could realize compliant force control under extreme configurations. It demonstrates that the humanoid manipulator can twist the steering wheel stably even in extreme configurations. It is the first exploration to operate a steering wheel similar to a human with a manipulator by using admittance control.

A Method of Human-Like Compliant Assembly Based on Variable Admittance Control for Space Maintenance

On-orbit assembly has become a crucial aspect of space operations, where the manipulator frequently and directly interacts with objects in a complex assembly process. The traditional manipulator control has limitations in adapting to diverse assembly tasks and is vulnerable to vibration, leading to assembly failure. To address this issue, we propose a human-like variable admittance control method based on the variable damping characteristics of the human arm. By collecting the velocity and contact force of human arm operations in assembly, we analyze the damping change of human arm and establish the active compliance model based on S-type damping variation rule in assembly. Furthermore, 3 passive contact models are proposed between the end of the human arm and the environment: one-sided bevel contact, both sides bevel contact, and pin-hole contact. On the basis of these active and passive models, a typical space assembly task for a robot is designed, and a human-like variable admittance controller is established and simulated. Finally, we build a ground verification platform and complete different assembly tasks, thereby successfully verifying the safety, robustness, and adaptability of the human-like variable admittance control method.

FC-EODR: Immersive Humanoid Dual-Arm Dexterous Explosive Ordnance Disposal Robot

In this study, we proposes a humanoid dual-arm explosive ordnance disposal (EOD) robot design. First, a seven-degree-of-freedom high-performance collaborative and flexible manipulator is developed, aiming at the transfer and dexterous operation of dangerous objects in EOD tasks. Furthermore, an immersive operated humanoid dual-arm dexterous explosive disposal robot (FC-EODR) is designed, which has a high passability to complex terrains such as low walls, slope roads, and stairs. It can remotely detect, manipulate, and remove explosives in dangerous environments through immersive velocity teleoperation. In addition, an autonomous tool-changing system is constructed, which enables the robot to flexibly switch between different tasks. The effectiveness of the FC-EODR is finally verified through a series of experiments, including the platform performance test, manipulator load test, teleoperated wire trimming, and screw-screwing experiments. This letter provides the technical foundation for robots to replace humans in EOD tasks and emergency situations.

Tracked Locomotion Systems for Ground Mobile Robots: A Review

The paper discusses the state-of-the-art of locomotion systems for ground mobile robots comprising tracks. Tracked locomotion, due to the large contact surface with the ground, is particularly suitable for tackling soft, yielding, and irregular terrains, but is characterized by lower speed and energy efficiency than wheeled locomotion, and lower obstacle-climbing capability than legged locomotion. Therefore, in recent years academic and industrial researchers have designed a wide variety of hybrid solutions, combining tracks with legs and wheels. The paper proposes three possible parallel taxonomies, based on body architecture, track profile, and track type, to help designers select the most suitable architecture on the basis of the operative necessities. Moreover, modeling, simulation, and design methodologies for tracked ground mobile robots are recalled.

Virtual Reality-Based Interface for Advanced Assisted Mobile Robot Teleoperation

This work proposes a new interface for the teleoperation of mobile robots based on virtual reality that allows a natural and intuitive interaction and cooperation between the human and the robot, which is useful for many situations, such as inspection tasks, the mapping of complex environments, etc. Contrary to previous works, the proposed interface does not seek the realism of the virtual environment but provides all the minimum necessary elements that allow the user to carry out the teleoperation task in a more natural and intuitive way. The teleoperation is carried out in such a way that the human user and the mobile robot cooperate in a synergistic way to properly accomplish the task: the user guides the robot through the environment in order to benefit from the intelligence and adaptability of the human, whereas the robot is able to automatically avoid collisions with the objects in the environment in order to benefit from its fast response. The latter is carried out using the well-known potential field-based navigation method. The efficacy of the proposed method is demonstrated through experimentation with the Turtlebot3 Burger mobile robot in both simulation and real-world scenarios. In addition, usability and presence questionnaires were also conducted with users of different ages and backgrounds to demonstrate the benefits of the proposed approach. In particular, the results of these questionnaires show that the proposed virtual reality based interface is intuitive, ergonomic and easy to use.