International Journal of Humanoid Robotics

The appropriate management of fall situations, i.e., fast instability detection, avoidance of unintentional falls, falling without damaging the body, fast recovery of the standing position after a fall-is an essential ability for biped humanoid robots. This issue is especially important for biped humanoid robots carrying out demanding movements such as walking on irregular surfaces, running, or playing a given sport. In this paper, we tackle the detection of instability, and the management of falls in biped humanoids using an integrated framework. In this framework, after instability is detected, a fall can be avoided, or at the very least, low-damage falling sequences can be triggered, depending on the degree of the detected instability. The proposed fall detection and fall avoidance methodologies have been validated in real-world experiments with biped humanoid robots (525 collision experiments were carried out). The obtained results show the robustness of the fall detection methodology. In addition, they show under which conditions falls can be avoided, and the reduction of the fall damage when a fall occurs. Besides, results also suggest that the proposed fall avoidance methodology still needs improvements. Moreover, the methodology is more suitable for small-sized and light-weight robots which are more mechanically robust to falling and can bear the required tests.

To be accepted as a part of our everyday lives, companion robots will require the capability to communicate socially, recognizing people's behavior and responding appropriately. In particular, we hypothesized that a humanoid robot should be able to recognize affectionate touches conveying liking or dislike because (a) a humanoid form elicits expectations of a high degree of social intelligence, (b) touch behavior plays a fundamental and crucial role in human bonding, and (c) robotic responses providing affection could contribute to people's quality of life. The hypothesis that people will seek to affectionately touch a robot needed to be verified because robots are typically not soft or warm like humans, and people can communicate through various other modalities such as vision and sound. The main challenge faced was that people's social norms are highly complex, involving behavior in multiple channels. To deal with this challenge, we adopted an approach in which we analyzed free interactions and also asked participants to rate short video-clips depicting human–robot interaction. As a result, we verified that touch plays an important part in the communication of affection from a person to a humanoid robot considered capable of recognizing cues in touch, vision, and sound. Our results suggest that designers of affectionate interactions with a humanoid robot should not ignore the fundamental modality of touch.

Moving the torso laterally in a walking biped robot can be mechanically more torque-efficient than not moving the torso according to recent research. Motivated by this observation, a torque-efficient torso-moving balance control strategy of a walking biped robot subject to a persistent continuous external force is suggested and verified in this paper. The torso-moving balance control strategy consists of a preliminary step and two additional steps. The preliminary step (disturbance detection) is to perceive the application of an external force by a safety boundary of zero moment point, detected approximately from cheap pressure sensors. Step 1 utilizes center of gravity (COG) Jacobian, centroidal momentum matrix and linear quadratic problem calculation to shift the zero moment point to the center of the support polygon. Step 2 makes use of H_∞ controllers for a more stable state shift from single support phase to double support phase. By comparing the suggested torso moving control strategy to the original control strategy that we suggested previously, a mixed balance control strategy is suggested. The strategy is verified through numerical simulation results.

Recent advances in control of humanoid robots have resulted in bipedal gaits that are dynamically stable on moderately rough terrain but are still limited to a small range of slopes. Humanoid robots, like humans, can take advantage of quadruped gaits to greatly extend this range. Cleverly designed gaits can provide robustness to rough terrain without requiring extensive feedback. In this paper, we present a robust crab-walking framework that includes forward and backward crawling patterns, rotation patterns, and sit-down and recovery sequences. The latter are activated autonomously once the robot detects that it tipped over. The performance and robustness of each locomotion pattern are investigated over a wide range of slopes. Crab-walking is shown to be especially adept at crawling forward on steep downward slopes (up to -54°) and crawling backward on steep upward slopes (up to 18°). Finally, we demonstrate the framework's autonomous capabilities by crossing the rough terrain in DARPA's virtual robotics challenge.

The workspace is a fundamental feature for a dexterous hand to grasping plan, motion control, and mechanical design. Although the graphic, numerical, or analytical methods are valid to generate the workspace of dexterous hands, but there exist several defects for these methods to describe the workspace characteristics, such as forms, boundaries, volumes, and intersection workspaces. We propose a combined modeling approach to visualize and analyze the workspace of YWZ dexterous hand, which has five fingers, 20 degrees of freedom (Dofs). The proposed approach is also fit for similar dexterous hands to generate their precise workspaces. After a brief mechanism introduction of YWZ dexterous hand, a displacement equation of its index finger is deduced to calculate the fingertip positions in three-dimension (3D) Euclidean space. Then, a two-dimension (2D) boundary figure enclosing the flexion–extension motion field of the finger is drawn by the displacement equation. Taking this boundary figure as a sketch in a CAD modeling environment, we further model a vivid 3D finger workspace, which is relative with the abduction–adduction motion of the finger. Besides, we generate the whole workspace of YWZ dexterous hand and analyze its volumes and intersection workspaces. The kinematic simulations and physical prototype experimentations are carried out to validate this approach can construct perfect workspace of dexterous hands. Compared with the Monte Carlo method, the form and boundary of the 3D finger workspace generated by our proposed approach have more accurate, integrated, vivid, and intuitional.

We can learn from the history of robotics that robots are getting closer to humans, both in the physical as well as in the social sense. The development line of robotics is marked with the triad: industrial — assistive — social robots, that leads from human–robot separation toward human–robot interaction. A social robot is a robot able to act autonomously and to interact with humans using social cues. A social robot that can assist a human for a longer period of time is called a robotic companion. This paper is devoted to the design and control issues of such a robotic companion, with reference to the robot FLASH designed at the Wroclaw University of Technology within the European project LIREC, and currently developed by the authors. Two HRI experiments with FLASH demonstrate the human attitude toward FLASH. A trial testing of the robot's emotional system is described.

Robots detect and keep track of relevant objects in their environment to accomplish some tasks. Many of them are equipped with mobile cameras as the main sensors, process the images and maintain an internal representation of the detected objects. We propose a novel active visual memory that moves the camera to detect objects in robot's surroundings and tracks their positions. This visual memory is based on a combination of multi-modal filters that efficiently integrates partial information. The visual attention subsystem is distributed among the software components in charge of detecting relevant objects. We demonstrate the efficiency and robustness of this perception system in a real humanoid robot participating in the RoboCup SPL competition.