Outlier-Robust State Estimation for Humanoid Robots*

Contemporary humanoids are equipped with visual and LiDAR sensors that are effectively utilized for Visual Odometry (VO) and LiDAR Odometry (LO). Unfortunately, such measurements commonly suffer from outliers in a dynamic environment, since frequently it is assumed that only the robot is in motion and the world is static. To this end, robust state estimation schemes are mandatory in order for humanoids to symbiotically co-exist with humans in their daily dynamic environments. In this article, the robust Gaussian Error-State Kalman Filter for humanoid robot locomotion is presented. The introduced method automatically detects and rejects outliers without relying on any prior knowledge on measurement distributions or finely tuned thresholds. Subsequently, the proposed method is quantitatively and qualitatively assessed in realistic conditions with the full-size humanoid robot WALK-MAN v2.0 and the mini-size humanoid robot NAO to demonstrate its accuracy and robustness when outlier VOLO measurements are present. Finally, in order to reinforce further research endeavours, our implementation is released as an open-source ROS/C++package

Sustainable food waste management in supermarkets

ood waste represents a significant burden to waste management systems, exacerbating food insecurity and contributing to global pollution, climate change, and biodiversity loss. Supermarkets bear partial responsibility for food waste, yet their sustainability efforts could also contribute to a solution. The present work aims at evaluating a sustainable approach to food waste management within supermarkets. To this end, we conducted a multi-criteria analysis, incorporating the perspectives of academic experts and 505 Italian consumers. Experts deemed residual value apps the most sustainable solution for food waste management in supermarkets, while also emphasising the influence of price and brand image. The consumer analysis corroborated these results. Specifically, consumers expressed a willingness to pay 36 % less for a bag of goods set to expire within 2–3 days, which increased to 60 % for goods set to expire within 24 h. The findings point to opportunities for mutual benefit between consumers and suppliers when food waste is effectively managed in store, thereby highlighting the need for further, product-focused research

Bipedal Walking Energy Minimization by Reinforcement Learning with Evolving Policy Parameterization

We present a learning-based approach for minimizing the electric energy consumption during walking of a passively-compliant bipedal robot. The energy consumption is reduced by learning a varying-height center-of-mass trajectory which uses efficiently the robots passive compliance. To do this, we propose a reinforcement learning method which evolves the policy parameterization dynamically during the learning process and thus manages to find better policies faster than by using fixed parameterization. The method is first tested on a function approximation task, and then applied to the humanoid robot COMAN where it achieves significant energy reduction. © 2011 IEEE

New Cross-Step Enabled Configurations for Humanoid Robot

This paper explores two new configurations for humanoid robot balancing and locomotion. Centroidal momentum manipulability analysis has been performed to study the features of the newly proposed configurations. Numerical simulations show that they outperform the regular ones in terms of angular momentum manipulability. More than that, the new configurations allow the humanoid robot to perform cross-step motions which is usually risky or mechanically impossible for most existing robots. However, cross-step introduces non-convex feasible region which makes it difficult to be incorporated into our existing step planner. Therefore, a simple heuristic has been proposed to help choosing a sub-convex region for the step planner. To validate the cross-step movement, walking simulations have been performed

Exploring Teleimpedance and Tactile Feedback for Intuitive Control of the Pisa/IIT SoftHand

This paper proposes a teleimpedance controller with tactile feedback for more intuitive control of the Pisa/IIT SoftHand. With the aim to realize a robust, efficient and low-cost hand prosthesis design, the SoftHand is developed based on the motor control principle of synergies, through which the immense complexity of the hand is simplified into distinct motor patterns. Due to the built-in flexibility of the hand joints, as the SoftHand grasps, it follows a synergistic path while allowing grasping of objects of various shapes using only a single motor. The DC motor of the hand incorporates a novel teleimpedance control in which the user's postural and stiffness synergy references are tracked in real-time. In addition, for intuitive control of the hand, two tactile interfaces are developed. The first interface (mechanotactile) exploits a disturbance observer which estimates the interaction forces in contact with the grasped object. Estimated interaction forces are then converted and applied to the upper arm of the user via a custom made pressure cuff. The second interface employs vibrotactile feedback based on surface irregularities and acceleration signals and is used to provide the user with information about the surface properties of the object as well as detection of object slippage while grasping. Grasp robustness and intuitiveness of hand control were evaluated in two sets of experiments. Results suggest that incorporating the aforementioned haptic feedback strategies, together with user-driven compliance of the hand, facilitate execution of safe and stable grasps, while suggesting that a low-cost, robust hand employing hardware-based synergies might be a good alternative to traditional myoelectric prostheses

HERI hand: A quasi dexterous and powerful hand with asymmetrical finger dimensions and under actuation

In this paper, the Hardware Embedded Reduced Intricacy (HERI) Hand, which is a novel tendon driven three-finger under-actuated hand demonstrating balanced dexterous finger manipulation and powerful grasping of common objects is presented. The third finger of HERI Hand is asymmetrically designed in terms of dimensions to emulate the functionality for combining middle finger, ring finger and little finger of a human hand. HERI Hand is equipped with three actuators devoted to the actuation of the flexion of the index finger and thumb, the flexion of the third finger and finally the thumb abduction and adduction motion with the latest drive having no interference with other transmissions. The proposed hand is capable of realizing delicate finger manipulation such as opening a lidded cup, which is super suitable to accomplish in such configuration. At the same time the hand demonstrates high grasping strength capacity thanks to the actuation sizing permitted by the under-actuated configuration. The hand is also equipped with tactile/pressure sensors distributed in the phalanxes, which leaves open the possibility of potential applications for sophisticated finger manipulations taking into account the phalanxes contact forces. Three different sets of experiments were carried out to demonstrate the performance of HERI Hand and validated its functionality

A torque-controlled humanoid robot riding on a two-wheeled mobile platform

This paper is motivated by the questions: What would happen if a humanoid robot is put on a Segway? Is it possible for the humanoid robot to use this transportation device that is specifically designed for human? Simulation involving a two-wheeled mobile platform (TWMP) and our humanoid robot COMAN (COmpliant HuMANoid Platform) shows that it is indeed feasible without any hardware modification. Regarding the implementation, the full dynamics of the humanoid robot is considered and quadratic optimization is employed to generate whole-body joint torques to realise two types of tasks according to the interaction type between the TWMP and the humanoid robot. The TWMP is considered as unknown disturbance and the humanoid robot has to keep balancing on it in the first type of task. On the contrary, the active movement of the humanoid robot is utilised as an interface to intuitively drive the TWMP in the second type of task. For both tasks, tracking the position of center of mass (CoM) and regulating the angular momentum around it are considered as primary objectives, stabilizing the posture of certain part of its body is optional. In addition, both tasks are repeated on uneven terrain to demonstrate the robustness of the control method