Humanoids 56.4 Manipulation 1315 trol.Customized computational hardware may help real time from the stereo cameras.This real-time mitigate this problem.For example,Sony's humanoid vision system has been used to detect floor ar- Part robot QRIO is equipped with a field-programmable eas,stair steps,and obstacles for navigation [56.43, 0 gate array (FPGA)to generate disparity maps in 44]. 3 56.4 Manipulation Hands and arms are the main interfaces with which one at the elbow,and three at the wrist.The use of seven humans act on the world around them.Manipulation DOFs results in a redundant degree of freedom with research within humanoid robotics typically focuses on respect to the six-DOF pose of the hand.To reduce me- the use of anthropomorphic arms,hands,and sensors chanical complexity,humanoid robot arms sometimes to perform tasks that are commonly performed by peo-have fewer than seven DOFs,for example,ARMAR- ple.Several chapters of the handbook relate to these III and Justin have seven-DOF arms,Cog and Domo goals,including Chap.24(Visual Servoing and Visual have six-DOF arms,and Asimo has five-DOF arms Tracking),Chap.26 (Motion for Manipulation Tasks),(Fig.56.16)[56.45,46]. and Chap.28(Grasping). Humanoid robot hands tend to vary more in their design (see Chap.15,Robot Hands).The human hand is 56.4.1 The Arm and Hand highly complex with over 20 DOFs(i.e.,approximately four DOFs per finger and a five-DOF thumb)in a very The kinematics of humanoid robot arms emulate the compact space with a compliant exterior,dense tactile human arm,which can be approximated by seven de-sensing,and muscular control.If a robot hand is to be grees of freedom(DOFs),with three at the shoulder, mounted on a robot arm,there are additional constraints in terms of the mass of the robot hand,since the hand sits at the end of the arm and must be efficiently moved in Fig.56.16 The humanoid robot Justin has two seven-DOF torque-controlled arms (DLR-Lightweight-Robot-III),and two 12-DOF hands (DLR-Hand-II).Justin's body is larger Fig.56.17 3-D object recognition by HRP-2 using versatile than a human's volumetric visionHumanoids 56.4 Manipulation 1315 trol. Customized computational hardware may help mitigate this problem. For example, Sony’s humanoid robot QRIO is equipped with a field-programmable gate array (FPGA) to generate disparity maps in real time from the stereo cameras. This real-time vision system has been used to detect floor ar￾eas, stair steps, and obstacles for navigation [56.43, 44]. 56.4 Manipulation Hands and arms are the main interfaces with which humans act on the world around them. Manipulation research within humanoid robotics typically focuses on the use of anthropomorphic arms, hands, and sensors to perform tasks that are commonly performed by peo￾ple. Several chapters of the handbook relate to these goals, including Chap. 24 (Visual Servoing and Visual Tracking), Chap. 26 (Motion for Manipulation Tasks), and Chap. 28 (Grasping). 56.4.1 The Arm and Hand The kinematics of humanoid robot arms emulate the human arm, which can be approximated by seven de￾grees of freedom (DOFs), with three at the shoulder, Fig. 56.16 The humanoid robot Justin has two seven-DOF torque-controlled arms (DLR-Lightweight-Robot-III), and two 12-DOF hands (DLR-Hand-II). Justin’s body is larger than a human’s one at the elbow, and three at the wrist. The use of seven DOFs results in a redundant degree of freedom with respect to the six-DOF pose of the hand. To reduce me￾chanical complexity, humanoid robot arms sometimes have fewer than seven DOFs, for example, ARMAR￾III and Justin have seven-DOF arms, Cog and Domo have six-DOF arms, and Asimo has five-DOF arms (Fig. 56.16) [56.45, 46]. Humanoid robot hands tend to vary more in their design (see Chap. 15, Robot Hands). The human hand is highly complex with over 20 DOFs (i. e., approximately four DOFs per finger and a five-DOF thumb) in a very compact space with a compliant exterior, dense tactile sensing, and muscular control. If a robot hand is to be mounted on a robot arm, there are additional constraints in terms of the mass of the robot hand, since the hand sits at the end of the arm and must be efficiently moved in Fig. 56.17 3-D object recognition by HRP-2 using versatile volumetric vision Part G 56.4