🤖 How to make a Robot That Can Write and Draw Like a Human
Humans learn handwriting by imitating letters and practicing strokes. Similarly, a robot…
A Multi-Modal Panoramic Attentional Model for Robots and Applications
Humanoid robots are becoming increasingly competent in perception of their surroundings and in providing intelligent responses to worldly events. A popular paradigm to realize such responses is the idea of attention itself. There are two important aspects of attention in the context of humanoid robots. First, perception describes how to design the sensory system to filter out useful salient features in the sensory field and perform subsequent higher level processing to perform tasks such as face recognition. Second, the behavioral response defines how the humanoid should act when it encounters the salient features. A model of attention enables the humanoid to achieve a semblance of liveliness that goes beyond exhibiting a mechanized repertoire of responses. It also facilitates progress in realizing models…
Grasp Planning for a Humanoid Hand
We focus on grasp planning for a humanoid multi-fingered hand attached at the tip of a humanoid robot’s arm. The hand has potential possibility to grasp various objects under several situations. Since the multi-fingered hand can use several grasp types such as fingertip grasp, and envelope grasp with taking the advantage of degrees of freedom. We develop grasp planner which selects a feasible grasp type based on the task, and determines contact positions for the fingers and the grasped object surface so that the fingers do not drop the object while staying with limited actuator capacity. To grasp an object, the robot first measures object position/orientation using vision sensor. Then, the planner plans the body motion to complete the grasping task based on vision sensor information. Even when the object’s location is not known beforehand, the robot should complete the grasping task as fast as possible. However, grasp planning with a humanoid robot is complex and often requires long calculation time. Hence, for the grasp planning, a heuristic but fast algorithm is preferred rather than precise but slow algorithms (Shimoga (1989)). Our planner calculates grasp motions within reasonable time by using predefined grasp types which are assigned with contacting finger links, desired sizes of the grasped object. Our planner selects a grasp type according to position/orientation of the grasped object similar to a human. As shown in Fig. 1 , a human grasps the side of the can with all fingers, grasps the top with fewer fingers. Failing to find feasible grasping posture using arm/hand kinematics alone, our planner attempts to do so using the full body kinematics. Using the degrees of freedom of full body, the planner has adaptable for reaching the object with the several…
Autonomous Motion Adaptation Against Structure Changes Without Model Identification
It is expected that humanoid robots provide various services to help human daily life such as household works, home security, medical care, welfare and so on(Dominey et al.,2007; Okada et al., 2003; 2005). In order to provide various services, humanoids have multi degree-of-freedom(DOF), sophisticated and complicated structure. These humanoid robots will work under human living environments which are not definable beforehand. So humanoids have to provide their given services under not only the designed environments but also unknown environments. Under unknown environments, robots cannot perform as planned, and they may fall or collide with obstacles. These impacts will wreak several unexpected structure changes such as gear cracks, joint locking, frame distortions and so on. Because of the designed motions are optimized to the robot structure, if the robot structure has changed, the services from robots cannot be provided. Because general users have no expertise knowledge of robots, thus, quick repairs under human living environments cannot be expected. Even in that case, it is expected that the robots should provide services to help human daily life as possible. In the case the humanoid robots cannot get rapid repair service, they have to provide the desired services with their broken body. In addition, using tools to provide some services can be considered as one of the structure changes. Therefore, it is necessary for future humanoids to obtain new motions which can provide the required services with changed structure. We propose an autonomous motion adaptation method which can be applied to sophisticated and complicated robots represented by humanoids. As a first step, we deal with the simple services based on trajectory control; services can be provided by following the correct path designed by experts. When robot structure has changed, achieving the designed trajectories on changed structure is needed. As the conventional methods, there are two typical approaches. One is the method based on model identification (El-Salam et al., 2005; Groom et al., 1999). Robots locate the occurred changes, identify the changed structure, recalculate inverse kinematics, and then obtain the proper motions. If the changed structure is identified, inverse kinematics leads the proper motions for new properties of changed structure. However, it is so difficult to identify the complicated structure changes in sophisticated robots. In additions, the available solving methods of inverse kinematics for multi DOF robots is non-existent according to the reference (The Robotics Society of Japan, 2005). So model identification method cannot be applied for humanoids. Another approach is the exploration method (Peters & Schaal, 2007); finding the new motions achieving the desired trajectories after structure has changed. In order to obtain the proper motions achieving the desired trajectories, joint angles are varied by trial and error. Injured robots will obtain the proper motions without complicated model identification, but this approach needs huge exploration costs. New motion adaptation method with low exploration costs and without model identification is needed. In this paper, we show one approach to adapt designed…
Development of Multi-Fingered Universal Robot Hand with Torque Limiter Mechanism
Today, various industrial robots are developed and used all over the world. However, these industrial robots are specialized in particular operations. In fact, one industrial robot is not able to be designed for operating various tasks. One of the causes is that general-purpose and multifunctional robot hands substituted human manual-handling task are not brought to realization. If these robot hands like human hands are consummated, the applicable field of industrial robots is extended, and the utilization efficiency is improved very much. A human hand has mechanical handling function such as grab, grip, pinch, push and pull. In addition, it can sense the feeling such as configuration, hard, flexible, smoothness and asperity. In other words, a human hand is a multifunctional and a universal end effector.…
