International Journal of Humanoid Robotics

In this paper, we propose standing and stepping control with switching rules based on angular momentum around the ankle for planar bipedal robots. A theoretical analysis under some approximation and mass distribution conditions shows that the proposed standing control maximizes stable regions. We can then classify the state of robots into the following three categories: (1) stabilizable via ankle torque; (2) unstabilizable only via ankle torque and stabilizable via ankle torque and trunk posture control; and (3) unstabilizable via ankle torque and trunk posture control. This criterion enables switching rules to appropriately switch robot control to balance control via ankle torque, balance control via ankle torque and trunk posture control, or stepping control. The proposed method is applicable to robots without feet. Simulation results demonstrate that the proposed method appropriately switches control according to the amplitudes of disturbances and maintains the balance of robots with and without feet.

This paper presents a general framework for locomotion control and generation of humanoid robots. Different from most of the existing work which uses the zero-moment point (2mp) to determine the feasibility of robot’s motion, we use the so-called contact wrench cone to derive motion feasibility conditions, whole-body motion controllers, and locomotion generators. The contact wrench cone consists of all feasible wrenches that can be applied to the robot through contacts, which provide allowable external forces and moments for realizing the robot’s motion. Algorithms are proposed to compute quantities defined on linear representations of a general convex cone, which can be various contact wrench cones as needed in developing motion generators and controllers. Based on the contact wrench cone for contact links and the proposed algorithms as well as a decomposition of the whole-body dynamics of a floating-base humanoid robot, we derive two motion tracking controllers. One controller contains a single quadratic program with linear inequality constraints, while the other consists of two quadratic programs which can be quickly solved by one of the proposed algorithms and in a closed form, respectively. Both controllers can be applied in real-time and achieve similar motion tracking performance in simulation. Based on contact wrench cones, furthermore, we derive two motion generation methods for humanoid robots. The first method adapts a reference motion, most often infeasible, to the robot by warping the motion’s time line so that the motion trajectory will remain the same but the velocity and acceleration profiles will be changed. The second method generates bipedal locomotion for given footsteps. All the proposed motion controllers and generators are applicable to general scenarios including uneven terrains and motions with the support of other links besides feet.

The proper description of finger-object contact state is critical to the analysis and control of multi-fingered hand grasping. At present, most studies assume that the finger-object contact state is invariable. However, in different stages of hand grasping, finger-object contact state is usually variable due to different contact factors, therefore, current finger-object contact models are not very suitable for describing it and the existing description and analysis of the hand grasping may be not appropriate. In this paper, we proposed a new method for describing and analyzing the multi-fingered hand grasping under various finger-object contact states, including a new finger-object contact model for describing the actual finger-object contact state, a grasp matrix for describing the hand grasping, and the condition number of the grasp matrix for analyzing the hand grasping. Taking a three-fingered hand grasping a sphere as an example, the hand grasping under four types of contact states was investigated. Simulations and experimental results both validated the effectiveness of the proposed method.

This paper presents an extension of previous model predictive control (MPC) schemes for dynamic walking to the stabilization of the time-varying divergent component-of-motion (DCM). In order to address the control authority limitations caused by fixed footholds, the step positions and rotations are treated as control inputs, allowing the generation and execution of stable walking motions, both at high speeds and in the face of disturbances. The use of the time-varying DCM allows consideration of height changes on the DCM dynamics, improving the robustness of the controller over varying terrain. Footstep rotation is included to allow for better modeling of the adjustment effects on reachability for stability and navigation of complex environments. This is done by formulating a quadratically constrained mixed-integer quadratic program (MIQCQP), which, when combined with the use of the time-varying DCM to account for the effects of height changes and use of angular momentum, improves the capabilities of MPC strategies for bipedal walking. While the MIQCQP cannot be solved at the desired control frequency, a method for compensating for the DCM dynamics between solves is presented. Simulation results of fast walking over flat ground and navigating varying-height terrain is presented with the ESCHER humanoid. This is combined with experiments that recover from a variety pushes, which demonstrate the effectiveness of this approach.

Robotic exoskeletons are expected to show high compliance and low impedance for human–robot interactions (HRIs). Our study introduces a novel method based on nonlinear model reference adaptive control (MRAC) to reduce the inherent impedance and replace the traditional impedance controller in HRIs. The control law and adaptive law are designed according to a candidate Lyapunov function. A simple system identification and initialization method for the nonlinear MRAC is put forward, which provides a set of better initial values for the controller. From the results of simulation and experiment, our controller can reduce the mechanical impedance and achieve high compliance for HRI. The adaptive control and compliance control can be both achieved by the proposed nonlinear MRAC framework.

This paper proposes an external force detection method for humanoid robot arm without using joint torque sensors, which can detect the external force of the joint space in real time during the operation of the robot. We first analyzed the structure of the humanoid robot arm we designed, and then established the external force detection model of the robot arm based on robot dynamics and motor dynamics. Subsequently, analyses were conducted on the error of the detection model and the dynamic model error of the robot arm is compensated by using the artificial neural network method to obtain more accurate external force value for the robot arm. In experiment, the accuracy test and the collision test were performed on the detected extern forces of the robot arm. The results show that the method can effectively improve the detection accuracy of the robot arm, and the robot arm can realize the real-time collision detection during its static and running states, which can ensure the safe operation of the robot.

The tactile sensing is of significant interest for coexisting-cooperative-cognitive robots (Tri-Co robots). In order to improve the tactile sensing performance of the robot via an electronic skin (e-skin), an auxiliary elastomeric substrate is required. This paper investigates the effect of the substrate including elastic modulus, thickness and location on the static sensing at first. It is found that thick substrate with small elastic modulus can even the force distribution effectively and improve the contact area sensing. But it brought noises and crosstalk on the e-skin when the substrate has the large deformation. In occasions of dynamic tactile sensing, the impact of substrate thickness and elastic modulus was also studied and it is found that smaller elastic modulus can help e-skin sense larger and higher frequency stimulus.

Among the possible fields in human society in which robotics can be applied, the possibility of a robotic guard has been imagined since long time. Human guards usually perform a range of tasks in which a robot can provide help. Security personnel not only perform security tasks and patrolling services, but also have to interact with people, providing additional information about the area they safeguard. In this paper, we present the design, development and preliminary tests of RobotMan, an anthropomorphic robot commissioned by a security company that should serve in security roles, such as patrolling large indoor areas and acting as a telepresence platform for the human guards, and guidance roles such as welcoming visitors and providing information. In the preliminary experiment, the new robot and a human guard were employed the roles of security and guidance in a manufacturing center. The results of the experiment collected from 96 participants highlighted differences in participants’ behavior when interacting with the robot rather than the human and a different perception of likeability and authority of the robot depending on subtle differences in its appearance and behavior. These results provide useful indication for the employment of robot guards in a real world situation.