In this paper, we introduce a method to estimate the magnitude of an external force applied on a humanoid robot. The approach does not require using force/torque sensors but instead uses measurements from commonly available forcesensing resistors (FSR) inserted under the feet of the humanoid robot. This approach is particularly interesting for affordable medium-sized humanoid robots such as Nao and Darwin-OP. The main idea is to use a simplified dynamic model of a linear inverted pendulum model (LIPM) subjected to an external force, and the information from the robot inertial measurement unit (IMU) and FSR sensors.The proposed method was validated on a Nao humanoid robot to estimate the external force applied in the sagittal plane through two experimental scenarios, and the results pointed out the efficiency of the proposed observer.

This paper aims at proposing a comprehensive control framework designed for cooperative transportation of a heavy load by two humanoid robots. First, a simplified dynamic model of the cooperative task is developed and the system stability is rigorously analyzed. Next, a centralized controller is formulated, this formulation provides an optimal control of the system by considering the robots dynamical stability while satisfying the robot-object-robot constraints. Finally, the controller is integrated with an arm controller and a local planner module forming a complete framework for cooperative transportation tasks. The approach is thoroughly analyzed and validated in simulation, and experiments are carried out on a team of two Nao humanoid robots transporting a range of objects placed on a small table. The experimental results pointed out the robustness of the approach as the robots successfully accomplished the transportation tasks in a stable way, moreover the transported objects masses were up to half the mass of one of the robot. Besides increasing the robot payload, some of the transported objects are relatively large and it is simply impossible for a single robot to transport them.

External force observer for humanoid robots has been widely studied in the literature. However, most of the proposed approaches generally rely on information from sixaxis force/torque sensors, which the small or medium-sized humanoid robots usually do not have. As a result, those approaches cannot be applied to this category of humanoid robots, which is widely used nowadays in education or research. In this paper, we improve the external force observer in [1] to handle the case of an external force applied in any direction and at an arbitrary point of the robot structure. The new observer is based on Kalman filter formulation and it allows the estimation of the three force components. The observer is simple to implement and can easily run in real time using the embedded processor of a medium-sized humanoid robot such as Nao or Darwin-OP. Moreover, the observer does not require any change to the robot hardware as it only uses measurements from the available force-sensing resistors (FSR) inserted under the feet of the humanoid robot and from the robot inertial measurement unit (IMU). The proposed observer was extensively validated on a Nao humanoid robot. In all conducted experiments, the observer successfully estimated the external force within a reasonable margin of error.

In this paper, we introduce a control strategy aimed at generating a stable walking pattern for a humanoid pushing a heavy load on a cart. In contrast to previous approaches that rely on force/torque sensors to measure the interaction between the robot and the pushed object, we present a simple model-based controller that can be implemented on most robots due to its computationally efficient design. Every aspect of the controller design is covered, from the formulation and validation of the dynamic model, to the implementation and validation on an actual humanoid robot. The experimental results show that the controller can efficiently make a NAO humanoid transport, in a stable way, the equivalent of its own weight on a rolling cart.

External force observer for humanoid robots has been widely studied in the literature. However, most of the proposed approaches generally rely on information from six-axis force/torque sensors, which the small or medium-sized humanoid robots usually do not have. As a result, those approaches cannot be applied to this category of humanoid robots, which are widely used nowadays in education or research. In this paper, we propose a Kalman filter-based observer to estimate the three components of an external force applied in any direction and at an arbitrary point of the robot’s structure. The observer is simple to implement and can easily run in real time using the embedded processor of a small or medium-sized humanoid robot such as Nao or Darwin-OP. Moreover, the observer does not require any changes to the robot’s hardware, as it only uses measurements from the available force-sensing resistors (FSR) inserted under the feet of the humanoid robot and from the robot’s inertial measurement unit (IMU). The proposed observer was extensively validated on a Nao humanoid robot in both cases of standing still or walking while an external force was applied to the robot. In the conducted experiments, the observer successfully estimated the external force within a reasonable margin of error. Moreover, the experimental data and the MATLAB and C++/ROS implementations of the proposed observer are available as an open source package. https://goo.gl/VkhejY.