Humanoid robot

About: Humanoid robot is a research topic. Over the lifetime, 14387 publications have been published within this topic receiving 243674 citations. The topic is also known as: 🤖.

A Floor and Obstacle Height Map for 3D Navigation of a Humanoid Robot

Abstract: With the development of biped robots, systems became able to navigate in a 3 dimensional world, walking up and down stairs, or climbing over small obstacles. We present a method for obtaining a labeled 2.5D grid map of the robot's surroundings. Each cell is marked either as floor or obstacle and contains a value telling the height of the floor or obstacle. Such height maps are useful for path planning and collision avoidance. The method uses a novel combination of a 3D occupancy grid for robust sensor data interpretation and a 2.5D height map for fine resolution floor values. We evaluate our approach using stereo vision on the humanoid robot QRIO and show the advantages over previous methods. Experimental results from navigation runs on an obstacle course demonstrate the ability of the method to generate detailed maps for autonomous navigation.

Realizing dynamic and efficient bipedal locomotion on the humanoid robot DURUS

Abstract: This paper presents the methodology used to achieve efficient and dynamic walking behaviors on the prototype humanoid robotics platform, DURUS. As a means of providing a hardware platform capable of these behaviors, the design of DURUS combines highly efficient electromechanical components with “control in the loop” design of the leg morphology. Utilizing the final design of DURUS, a formal framework for the generation of dynamic walking gaits which maximizes efficiency by exploiting the full body dynamics of the robot, including the interplay between the passive and active elements, is developed. The gaits generated through this methodology form the basis of the control implementation experimentally realized on DURUS; in particular, the trajectories generated through the formal framework yield a feedforward control input which is modulated by feedback in the form of regulators that compensate for discrepancies between the model and physical system. The end result of the unified approach to control-informed mechanical design, formal gait design and regulator-based feedback control implementation is efficient and dynamic locomotion on the humanoid robot DURUS. In particular, DURUS was able to demonstrate dynamic locomotion at the DRC Finals Endurance Test, walking for just under five hours in a single day, traveling 3.9 km with a mean cost of transport of 1.61—the lowest reported cost of transport achieved on a bipedal humanoid robot.

Real-time CAD model matching for mobile manipulation and grasping

Abstract: Humanoid robotic assistants need capable and comprehensive perception systems that enable them to perform complex manipulation and grasping tasks. This requires the identification and recognition of supporting planes and objects in the world, together with their precise 6D poses. In this paper, we propose a 3D perception system architecture that can robustly fit CAD models in cluttered table setting scenes for the purpose of grasping with a mobile manipulator. Our approach uses a powerful combination of two different camera technologies, Time-Of-Flight (TOF) and RGB, to robustly segment the scene and extract object clusters. Using an a-priori database of object models we then perform a CAD matching in 2D camera images. We validate the proposed system in a number of experiments, and compare the system's performance and reliability with similar initiatives.

Drift-free humanoid state estimation fusing kinematic, inertial and LIDAR sensing

Abstract: This paper describes an algorithm for the probabilistic fusion of sensor data from a variety of modalities (inertial, kinematic and LIDAR) to produce a single consistent position estimate for a walking humanoid. Of specific interest is our approach for continuous LIDAR-based localization which maintains reliable drift-free alignment to a prior map using a Gaussian Particle Filter. This module can be bootstrapped by constructing the map on-the-fly and performs robustly in a variety of challenging field situations. We also discuss a two-tier estimation hierarchy which preserves registration to this map and other objects in the robot's vicinity while also contributing to direct low-level control of a Boston Dynamics Atlas robot. Extensive experimental demonstrations illustrate how the approach can enable the humanoid to walk over uneven terrain without stopping (for tens of minutes), which would otherwise not be possible. We characterize the performance of the estimator for each sensor modality and discuss the computational requirements.

Biped walking robots created at Waseda University: WL and WABIAN family.

Abstract: This paper proposes the mechanism and control of the biped humanoid robots WABIAN-RIV and WL-16. WABIAN-RIV has 43 mechanical degrees of freedom (d.f.): 6 d.f. in each leg, 7 d.f. in each arm, 3 d.f. in each hand, 2 d.f. in each eye, 4 d.f. in the neck and 3 d.f. in the waist. Its height is about 1.89 m and its total weight is 127 kg. It has a vision system and a voice recognition system to mimic some of the capabilities of the human senses. WL-16 consists of a pelvis and two legs having six 1 d.f. active linear actuators. An aluminium chair is mounted on two sets of its telescopic poles. To reduce the large support forces during the support phase, a support torque reduction mechanism is developed, which is composed of two compression gas springs with different stiffness. For the stability of the robots, a compensatory motion control algorithm is developed. This control compensates for moments generated by the motion of the lower limbs, using the motion of the trunk and the waist that is obtained by the zero moment point concept and fast Fourier transform. WABIAN-RIV is able to walk forwards, backwards and sideways, dance, carry heavy goods and express emotion, etc. WL-16 can move forwards, backwards and sideways while carrying an adult weighing up to 60 kg.