As described in this paper, we propose a new haptic interface for a service robot. For safety with service robots working in a space where people live, some notification before collision with an obstacle is desirable....As described in this paper, we propose a new haptic interface for a service robot. For safety with service robots working in a space where people live, some notification before collision with an obstacle is desirable. To achieve such a function, we developed a master-slave manipulator system in which the slave manipulator surface is covered with many proximity sensors. Additionally, we developed a haptic device that feeds back proximity sense information to the operator using small vibration motors. We attached the haptic device to the arm of the operator and vibrated the vibration motor corresponding to the sensor. Thereby, the operator was able to ascertain the position of an object near the manipulator, and to make the robot maneuver to avoid it before collision. To confirm the system usefulness, we equipped subjects with the developed proximity sense presentation device and performed a detection-position-specific experiment and an obstacle avoidance experiment in a narrow space. As results of the detection position specific experiment on five subjects, four subjects reported the detection position correctly. The remaining one person failed because of his particular arm shape. Operation experiments conducted in a narrow space showed that all subjects＇ work was successful when given feedback of proximity sense information. Nobody was successful without proximity sense information. Results of these two experiments demonstrate that this proposed system is useful for obstacle avoidance of a master-slave manipulator system.展开更多
Brain-machine interface (BMI) has been developed due to its possibility to cure severe body paralysis. This technology has been used to realize the direct control of prosthetic devices,such as robot arms,computer curs...Brain-machine interface (BMI) has been developed due to its possibility to cure severe body paralysis. This technology has been used to realize the direct control of prosthetic devices,such as robot arms,computer cursors,and paralyzed muscles. A variety of neural decoding algorithms have been designed to explore relationships between neural activities and movements of the limbs. In this paper,two novel neural decoding methods based on probabilistic neural network (PNN) in rats were introduced,the PNN decoder and the modified PNN (MPNN) decoder. In the ex-periment,rats were trained to obtain water by pressing a lever over a pressure threshold. Microelectrode array was implanted in the motor cortex to record neural activity,and pressure was recorded by a pressure sensor synchronously. After training,the pressure values were estimated from the neural signals by PNN and MPNN decoders. Their per-formances were evaluated by a correlation coefficient (CC) and a mean square error (MSE). The results show that the MPNN decoder,with a CC of 0.8657 and an MSE of 0.2563,outperformed the traditionally-used Wiener filter (WF) and Kalman filter (KF) decoders. It was also observed that the discretization level did not affect the MPNN performance,indicating that the MPNN decoder can handle different tasks in BMI system,including the detection of movement states and estimation of continuous kinematic parameters.展开更多
We propose a scheme to manipulate a topological spin qubit which is realized with cold atoms in a one-dimensional optical lattice.In particular, by introducing a quantum opto-electro-mechanical interface, we are able ...We propose a scheme to manipulate a topological spin qubit which is realized with cold atoms in a one-dimensional optical lattice.In particular, by introducing a quantum opto-electro-mechanical interface, we are able to first transfer a superconducting qubit state to an atomic qubit state and then to store it into the topological spin qubit. In this way, an efficient topological quantum memory could be constructed for the superconducting qubit. Therefore, we can consolidate the advantages of both the noise resistance of the topological qubits and the scalability of the superconducting qubits in this hybrid architecture.展开更多
文摘As described in this paper, we propose a new haptic interface for a service robot. For safety with service robots working in a space where people live, some notification before collision with an obstacle is desirable. To achieve such a function, we developed a master-slave manipulator system in which the slave manipulator surface is covered with many proximity sensors. Additionally, we developed a haptic device that feeds back proximity sense information to the operator using small vibration motors. We attached the haptic device to the arm of the operator and vibrated the vibration motor corresponding to the sensor. Thereby, the operator was able to ascertain the position of an object near the manipulator, and to make the robot maneuver to avoid it before collision. To confirm the system usefulness, we equipped subjects with the developed proximity sense presentation device and performed a detection-position-specific experiment and an obstacle avoidance experiment in a narrow space. As results of the detection position specific experiment on five subjects, four subjects reported the detection position correctly. The remaining one person failed because of his particular arm shape. Operation experiments conducted in a narrow space showed that all subjects＇ work was successful when given feedback of proximity sense information. Nobody was successful without proximity sense information. Results of these two experiments demonstrate that this proposed system is useful for obstacle avoidance of a master-slave manipulator system.
基金Project supported by the National Natural Science Foundation of China (Nos. 30800287 and 60703038)the Natural Science Foundation of Zhejiang Province, China (No. Y2090707)
文摘Brain-machine interface (BMI) has been developed due to its possibility to cure severe body paralysis. This technology has been used to realize the direct control of prosthetic devices,such as robot arms,computer cursors,and paralyzed muscles. A variety of neural decoding algorithms have been designed to explore relationships between neural activities and movements of the limbs. In this paper,two novel neural decoding methods based on probabilistic neural network (PNN) in rats were introduced,the PNN decoder and the modified PNN (MPNN) decoder. In the ex-periment,rats were trained to obtain water by pressing a lever over a pressure threshold. Microelectrode array was implanted in the motor cortex to record neural activity,and pressure was recorded by a pressure sensor synchronously. After training,the pressure values were estimated from the neural signals by PNN and MPNN decoders. Their per-formances were evaluated by a correlation coefficient (CC) and a mean square error (MSE). The results show that the MPNN decoder,with a CC of 0.8657 and an MSE of 0.2563,outperformed the traditionally-used Wiener filter (WF) and Kalman filter (KF) decoders. It was also observed that the discretization level did not affect the MPNN performance,indicating that the MPNN decoder can handle different tasks in BMI system,including the detection of movement states and estimation of continuous kinematic parameters.
基金supported by the National Fundamental Research Programm of China(Grants Nos.2013CB921804 and 2012CB921604)the National Natural Science Foundation of China(Grant Nos.11474153,11274069,11474064,61435007 and 11474177)+1 种基金the Program for Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China(Grant No.IRT1243)the Research Grants Council of Hong Kong(Grant Nos.HKU173051/14P and HKU173055/15P)
文摘We propose a scheme to manipulate a topological spin qubit which is realized with cold atoms in a one-dimensional optical lattice.In particular, by introducing a quantum opto-electro-mechanical interface, we are able to first transfer a superconducting qubit state to an atomic qubit state and then to store it into the topological spin qubit. In this way, an efficient topological quantum memory could be constructed for the superconducting qubit. Therefore, we can consolidate the advantages of both the noise resistance of the topological qubits and the scalability of the superconducting qubits in this hybrid architecture.
