CN115431264A - Interactive motion control method and system with individual characteristics - Google Patents
Interactive motion control method and system with individual characteristics Download PDFInfo
- Publication number
- CN115431264A CN115431264A CN202210956939.XA CN202210956939A CN115431264A CN 115431264 A CN115431264 A CN 115431264A CN 202210956939 A CN202210956939 A CN 202210956939A CN 115431264 A CN115431264 A CN 115431264A
- Authority
- CN
- China
- Prior art keywords
- motion
- robot
- user
- time
- acceleration
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000033001 locomotion Effects 0.000 title claims abstract description 195
- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000002452 interceptive effect Effects 0.000 title claims abstract description 17
- 230000008878 coupling Effects 0.000 claims abstract description 23
- 238000010168 coupling process Methods 0.000 claims abstract description 23
- 238000005859 coupling reaction Methods 0.000 claims abstract description 23
- 230000001133 acceleration Effects 0.000 claims description 30
- 238000005070 sampling Methods 0.000 claims description 23
- 238000004364 calculation method Methods 0.000 claims description 5
- 230000007704 transition Effects 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 13
- 230000000694 effects Effects 0.000 abstract description 6
- 241000282414 Homo sapiens Species 0.000 description 6
- 230000006870 function Effects 0.000 description 5
- 230000006399 behavior Effects 0.000 description 4
- 230000003993 interaction Effects 0.000 description 4
- 238000011160 research Methods 0.000 description 3
- 241001342895 Chorus Species 0.000 description 2
- 230000008451 emotion Effects 0.000 description 2
- 230000003997 social interaction Effects 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000010355 oscillation Effects 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 230000001020 rhythmical effect Effects 0.000 description 1
- 230000002269 spontaneous effect Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000001755 vocal effect Effects 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1661—Programme controls characterised by programming, planning systems for manipulators characterised by task planning, object-oriented languages
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J13/00—Controls for manipulators
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
Landscapes
- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Manipulator (AREA)
Abstract
The invention relates to the field of robot motion control, and provides an interactive motion control method and system with individual characteristics, which comprises the following steps: s1: acquiring personal motion characteristics, designing an intention coupling item, and constructing a virtual teacher motion frame through the personal motion characteristics and the intention coupling item; s2: the virtual teacher motion frame acquires the motion trail of the user in real time, and the robot is controlled to move along by the motion trail of the user. The invention can select different personal motion characteristics according to different participants to control the teaching process of the virtual teacher, so that the learning of different participants is more targeted, thereby improving the effect of the motion learning; in addition, different motion modes can be taught by changing the intention coupling item, introduction of various teaching models is achieved, and compared with a real teacher, the virtual teacher has lower teaching cost while achieving an individualized learning process.
Description
Technical Field
The invention relates to the field of robot motion control, in particular to an interactive motion control method and system with individual characteristics.
Background
Interpersonal coordination is a natural bridge for individuals to collaborate with others, and it is derived from a dynamic and complex set of specialized processes involving adaptive non-verbal behaviors, emotions, actions, emotions, and the like. In the research on human interpersonal interaction, different individuals have different degrees of difference in motion coordination level, and coordination level between individuals with similar motion characteristics is higher, so that it is desirable to design a virtual robot capable of interacting with human beings, guiding the motion of participants and trying to improve the motion coordination level of the individual participants. .
In real life, new behaviors are typically created with the help of more specialized partners, such as creating new personal coordination patterns in choruses such as making social dances or choruses. Previous studies have attempted to explore the learning of new stable collaborative patterns by participants using finger rhythmic telescoping movements. A common stable mode of finger pinching is either in-phase or in-phase with the two fingers, with the participant learning a stable phase generally between 0 degrees in-phase and 180 degrees in-phase. After disturbance, if the learned coordination mode can still be performed, the learning effect is good.
A series of previous studies have shown that sensorimotor synchrony between individuals may play a crucial role in successful social interactions, and spontaneous and induced synchrony have been shown to have a strong impact on the quality of social interactions. A higher level of motion coordination means a better motion interaction effect. Mirror games of motion interaction between human individuals and robots have been adopted as a typical example by several research groups, and all these studies show that two moving parties with similar individual motion characteristics exhibit greater synchronicity. The robot has different functions by selecting different control input items, and on the basis of synchronous motion, the robot is expected to act as a virtual teacher by introducing an intention coupling item into the control input, so that the robot can teach a new motion mode of a participant in the interactive motion process, and the motion mode of the participant is gradually guided to a motion mode with high coordination level. To this end, a new idea is provided for improving the individual movement coordination level, and a robot, namely a virtual player, needs to be designed to be a virtual teacher role by giving a determined intention coupling item so as to guide participants to learn a new movement mode. Meanwhile, the virtual teacher can be endowed with personal motion characteristics, so that the motion of the virtual teacher is closer to that of human beings, and the human beings are better guided to carry out motion coordination and learning.
The prior art does not consider the influence of personal motion characteristics on motion coordination, so that the behavior of a virtual player is not vivid enough, and the effect of coordinated motion cannot be expected experimentally.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
In order to solve the above technical problem, the present invention provides an interactive motion control method with individual characteristics, comprising:
s1: acquiring personal motion characteristics, designing an intention coupling item, and constructing a virtual teacher motion frame through the personal motion characteristics and the intention coupling item;
s2: the virtual teacher motion frame acquires the motion trail of the user in real time, and the robot is controlled to move along by the motion trail of the user.
Preferably:
the intention coupling term C int The expression of (a) is:
wherein c (t) is an exponential function of personal motion characteristics, t is sampling time, phi represents a phase difference between motion made by a user and motion made by a robot,is the speed of movement, x, of the user hp Is the position of the user or the like,is the speed of movement of the robot.
Preferably, step S2 specifically includes:
s21: the virtual teacher motion frame acquires the position of a user and the acceleration of the robot;
s22: calculating to obtain the movement speed of the user and the acceleration of the user according to the position of the user, and calculating to obtain the position of the robot and the movement speed of the robot according to the acceleration of the robot;
s23: the virtual teacher motion frame controls the robot to move along with the virtual teacher motion frame through the motion speed of the user, the acceleration of the user, the position of the robot and the motion speed of the robot, and the motion of the robot is adjusted through boundary conditions.
Preferably, in step S22, the calculation formula of the movement speed of the user and the acceleration of the user is:
wherein k is a sampling number,the motion speed of the user for the kth sample,the motion speed of the user for the k-1 th sample,is the acceleration, x, of the user sampled for the kth time hp (k) Position of user for the k-th sampling, x hp (k-1) is the position of the user sampled at the k-1 st time, and t is the sampling time.
Preferably, in step S22, the calculation formula of the position of the robot and the movement speed of the robot is:
wherein k is a sampling number,the motion speed of the robot for the kth sample,speed of movement, x, of the robot for the k-1 th sample vp (k) Position of the robot for the kth sample, x vp (k-1) is the position of the robot sampled at the k-1 st time,the acceleration of the robot sampled at the k-1 st time, and t is the sampling time.
Preferably, in step S23, the expression of the virtual teacher motion frame controlling the motion of the robot is:
wherein,is the acceleration of the robot;for movement of robotsSpeed; alpha, beta and gamma are motion control parameters, and omega is the eigenfrequency of motion; c int Coupling terms for intent; v is a pre-recorded personal speed time sequence; c (t) is a function of the transition time; t is 0 To the conversion time; t is 1 Is the end time of the transition; τ is the time constant.
Preferably, in step S23, the expression of the boundary condition is:
wherein k is a sample number, k is a sampling number,the acceleration of the robot sampled at the k-1 st time,acceleration of the robot, x, sampled for the kth time vp And epsilon is the position of the robot, epsilon is a control trigger condition, and L (1) = -1, L (2) =1 is a boundary condition of the motion of the robot.
An interactive motion control system having individual features, comprising:
the frame building module is used for obtaining personal motion characteristics, designing an intention coupling item and building a virtual teacher motion frame through the personal motion characteristics and the intention coupling item;
and the motion control module is used for acquiring the motion trail of the user in real time by the virtual teacher motion frame and controlling the robot to follow the motion according to the motion trail of the user.
The invention has the following beneficial effects:
1. the invention can select different personal motion characteristics according to different participants to control the teaching process of the virtual teacher, so that the learning of different participants is more pertinent, and the effect of the motion learning is improved;
2. in addition, different movement modes can be taught by changing the intention coupling item, introduction of various teaching models is achieved, and compared with a real teacher, the virtual teacher has lower teaching cost while achieving an individualized learning process.
Drawings
FIG. 1 is a flow chart of a method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of simple harmonic motions made by a user and a robot;
FIG. 3 is a position time series and velocity time series of user and robot motion;
FIG. 4 is a statistical analysis of RMSE (position synchronization error) values;
FIG. 5 is a statistical analysis of CV (phase stability) values;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
Referring to fig. 1, the present invention provides an interactive motion control method having an individual characteristic, including:
s1: acquiring personal motion characteristics, designing an intention coupling item, and constructing a virtual teacher motion frame through the personal motion characteristics and the intention coupling item;
specifically, the personal motion characteristics are obtained in the following manner: one user independently performs one-dimensional simple harmonic motion by using a mouse, records the position time sequence of the motion, processes the position time sequence to obtain the speed time sequence of the user so as to obtain a speed probability distribution map of the user, and describes the personal motion characteristics of the user by using the speed probability distribution map of the user, wherein previous researches prove that the personal motion characteristics of each person are kept unchanged;
s2: the virtual teacher motion frame acquires the motion trail of a user in real time, and the robot is controlled to follow the motion trail of the user;
specifically, the motion control system of the robot uses a Haken-Kelso-Bunz (HKB) oscillator which combines a Rayleigh oscillator and a Van der pol oscillator, and the HKB oscillator has a stable limit ring, and simultaneously, the amplitude of motion is reduced along with the increase of the motion speed, so that the motion characteristics of periodic oscillation of the human trunk are met.
In this embodiment:
the intention coupling term C int The expression of (c) is:
wherein c (t) is an exponential function of personal motion characteristics, t is sampling time, phi represents the phase difference between the motion of the user and the motion of the robot,is the speed of movement, x, of the user hp Is the position of the user or the like,is the movement speed of the robot.
In this embodiment, step S2 specifically includes:
s21: the virtual teacher motion frame acquires the position of a user and the acceleration of the robot;
s22: calculating the position of the user to obtain the movement speed of the user and the acceleration of the user, and calculating the position of the robot and the movement speed of the robot through the acceleration of the robot;
s23: the virtual teacher motion frame controls the robot to follow the motion through the motion speed of the user, the acceleration of the user, the position of the robot and the motion speed of the robot, and the motion of the robot is adjusted through boundary conditions;
specifically, the robot is controlled by the virtual teacher motion frame, so that simple harmonic motion performed by the user and the robot always keeps a set phase difference, the motion form is shown in fig. 2, HP is the position of the user, and VP is the position of the robot; the position time series and the velocity time series of the user and the robot movement are shown in fig. 3.
In this embodiment, in step S22, the calculation formula of the motion speed of the user and the acceleration of the user is:
wherein k is a sampling number,the motion speed of the user for the kth sample,the motion speed of the user for the k-1 th sample,is the acceleration, x, of the user sampled for the kth time hp (k) Is the location, x, of the user sampled at the kth time hp (k-1) is the position of the user sampled at the k-1 st time, and t is the sampling time.
In this embodiment, in step S22, the calculation formula of the position of the robot and the movement speed of the robot is:
wherein k is a sample number, k is a sampling number,is the movement speed of the robot sampled at the kth time,speed of movement, x, of the robot for the k-1 th sample vp (k) Position of the robot for the kth sample, x vp (k-1) is the position of the robot sampled at the k-1 st time,the acceleration of the robot sampled at the k-1 st time, and t is the sampling time.
In this embodiment, in step S23, the expression of the virtual teacher motion frame controlling the motion of the robot is as follows:
wherein,is the acceleration of the robot;is the movement speed of the robot; alpha, beta and gamma are motion control parameters, and omega is the eigenfrequency of motion; c int An intent-coupled term for maintaining a particular motion coordination pattern; v is a pre-recorded personal speed time sequence used for representing personal motion characteristics; c (t) is a conversion time function used for an over-learning process and a subsequent autonomous movement process; t is a unit of 0 For the switching time, it is preferably set to 30s; t is 1 Is the end time of the transition; τ is a time constant.
In this embodiment, in step S23, the expression of the boundary condition is:
wherein k is a sampling number,is the acceleration of the robot sampled at the k-1 st time,acceleration of the robot, x, for the kth sample vp Is the position of the robot, epsilon is a control trigger condition, and L (1) = -1, L (2) =1 is a boundary condition of the motion of the robot; when the motion position of the robot is close to or exceeds two boundaries, the motion planning module in the robot is updated in time to enable the robot to move in the opposite direction.
After a user experiences long-term motion interaction with the robot, the user learns the ability of perceiving and imitating the behaviors of other people, namely the social ability, and in order to verify the ability, a series of performance indexes are designed to measure the improvement condition of the social ability of the user.
Wherein x is 1,j Is the position of the robot at the jth sample; x is the number of 2,j Is the location of the jth sampling user; n is the total number of samples in the experiment; the RMSE (position synchronization error) is used for describing the position synchronization of both moving parties, and the lower the RMSE value is, the better the effect of representing the movement position synchronization is; the RMSE of the robot in the training phase and the presentation phase for four different individual movement characteristics is shown in fig. 4.
Wherein, Δ Φ i The phase difference of the motion tracks of the participant and the robot at the ith sampling point is obtained; the | · | | is a two-norm for solving the average value of the whole sampling; CV (phase stability) measures the phase stability of the motion tracks of the two, and the higher the CV value is, the more stable the motion phase is kept; the CV of the robot in the training stage and the demonstration stage under four different individual motion characteristics are shown in fig. 5.
The present invention provides an interactive motion control system with individual features, comprising:
the frame building module is used for obtaining personal motion characteristics, designing an intention coupling item and building a virtual teacher motion frame through the personal motion characteristics and the intention coupling item;
and the motion control module is used for acquiring the motion trail of the user in real time by the virtual teacher motion frame and controlling the robot to follow the motion according to the motion trail of the user.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or system comprising the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments. In the unit claims enumerating several means, several of these means can be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order, but rather the words first, second, etc. are to be interpreted as indicating.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (8)
1. An interactive motion control method having an individual characteristic, comprising:
s1: acquiring personal motion characteristics, designing an intention coupling item, and constructing a virtual teacher motion frame through the personal motion characteristics and the intention coupling item;
s2: the virtual teacher motion frame acquires the motion trail of the user in real time, and the robot is controlled to follow the motion trail of the user.
2. The interactive motion control method with personality according to claim 1, wherein:
the intention coupling term C int The expression of (a) is:
wherein c (t) is an exponential function of personal motion characteristics, t is sampling time, phi represents a phase difference between motion made by a user and motion made by a robot,is the speed of movement, x, of the user hp Is the location of the user or users,is the movement speed of the robot.
3. The interactive motion control method with individual characteristics according to claim 1, wherein the step S2 is specifically:
s21: the virtual teacher motion frame acquires the position of a user and the acceleration of the robot;
s22: calculating to obtain the movement speed of the user and the acceleration of the user according to the position of the user, and calculating to obtain the position of the robot and the movement speed of the robot according to the acceleration of the robot;
s23: the virtual teacher motion frame controls the robot to move along with the virtual teacher motion frame through the motion speed of the user, the acceleration of the user, the position of the robot and the motion speed of the robot, and the motion of the robot is adjusted through boundary conditions.
4. The interactive motion control method with individual characteristics according to claim 3, wherein in step S22, the calculation formula of the motion velocity of the user and the acceleration of the user is:
wherein k is a sample number, k is a sampling number,the motion speed of the user for the kth sample,the motion speed of the user for the k-1 th sample,acceleration of the user for the kth sample, x hp (k) Position of user for the k-th sampling, x hp (k-1) is the position of the user sampled at the k-1 st time, and t is the sampling time.
5. The interactive motion control method with individual characteristics according to claim 3, wherein in step S22, the position of the robot and the motion velocity of the robot are calculated by the following formulas:
wherein k is a sample number, k is a sampling number,the motion speed of the robot for the kth sample,speed of movement, x, of the robot for the k-1 th sample vp (k) Position of the robot for the kth sample, x vp (k-1) is the position of the robot sampled at the k-1 st time,the acceleration of the robot sampled at the k-1 st time, and t is the sampling time.
6. The interactive motion control method with individual characteristics according to claim 3, wherein in step S23, the expression of the virtual teacher motion frame controlling the motion of the robot is:
wherein,is the acceleration of the robot;is the movement speed of the robot; alpha, beta and gamma are motion control parameters, and omega is the eigenfrequency of motion; c int Coupling terms for intent; v is a pre-recorded personal speed time sequence; c (t) is a function of the transition time; t is 0 To the conversion time; t is 1 Is the end time of the transition; τ is the time constant.
7. The interactive motion control method with individual features of claim 3, wherein in step S23, the expression of the boundary condition is:
8. An interactive motion control system having individual features, comprising:
the frame building module is used for obtaining personal motion characteristics, designing an intention coupling item and building a virtual teacher motion frame through the personal motion characteristics and the intention coupling item;
and the motion control module is used for acquiring the motion trail of the user in real time by the virtual teacher motion frame and controlling the robot to follow the motion trail of the user.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210956939.XA CN115431264B (en) | 2022-08-10 | 2022-08-10 | Interactive motion control method and system with individual features |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210956939.XA CN115431264B (en) | 2022-08-10 | 2022-08-10 | Interactive motion control method and system with individual features |
Publications (2)
Publication Number | Publication Date |
---|---|
CN115431264A true CN115431264A (en) | 2022-12-06 |
CN115431264B CN115431264B (en) | 2024-07-09 |
Family
ID=84242213
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210956939.XA Active CN115431264B (en) | 2022-08-10 | 2022-08-10 | Interactive motion control method and system with individual features |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN115431264B (en) |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2005297095A (en) * | 2004-04-07 | 2005-10-27 | Sony Corp | Robot device and its action comparison method |
CN111009318A (en) * | 2019-11-25 | 2020-04-14 | 上海交通大学 | Virtual reality technology-based autism training system, method and device |
CN112123334A (en) * | 2020-08-24 | 2020-12-25 | 中国地质大学(武汉) | Interactive arm control method and system based on event-driven mechanism |
CN113096805A (en) * | 2021-04-12 | 2021-07-09 | 华中师范大学 | Autism emotion cognition and intervention system |
CN113771043A (en) * | 2021-09-30 | 2021-12-10 | 上海傅利叶智能科技有限公司 | Control method and device for enabling robot to follow virtual object and rehabilitation robot |
CN113858201A (en) * | 2021-09-29 | 2021-12-31 | 清华大学 | Intention-driven adaptive impedance control method, system, device, storage medium and robot |
CN114675541A (en) * | 2022-03-31 | 2022-06-28 | 中国地质大学(武汉) | Biological heuristic two-dimensional limb cooperative control method and system |
-
2022
- 2022-08-10 CN CN202210956939.XA patent/CN115431264B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2005297095A (en) * | 2004-04-07 | 2005-10-27 | Sony Corp | Robot device and its action comparison method |
CN111009318A (en) * | 2019-11-25 | 2020-04-14 | 上海交通大学 | Virtual reality technology-based autism training system, method and device |
CN112123334A (en) * | 2020-08-24 | 2020-12-25 | 中国地质大学(武汉) | Interactive arm control method and system based on event-driven mechanism |
CN113096805A (en) * | 2021-04-12 | 2021-07-09 | 华中师范大学 | Autism emotion cognition and intervention system |
CN113858201A (en) * | 2021-09-29 | 2021-12-31 | 清华大学 | Intention-driven adaptive impedance control method, system, device, storage medium and robot |
CN113771043A (en) * | 2021-09-30 | 2021-12-10 | 上海傅利叶智能科技有限公司 | Control method and device for enabling robot to follow virtual object and rehabilitation robot |
CN114675541A (en) * | 2022-03-31 | 2022-06-28 | 中国地质大学(武汉) | Biological heuristic two-dimensional limb cooperative control method and system |
Non-Patent Citations (1)
Title |
---|
赵剑辉;陈卓铭;周萍;黄伟新;王玉意;: "多感官互动训练***的设计与开发", 中国医疗设备, no. 10, 15 October 2009 (2009-10-15), pages 20 - 44 * |
Also Published As
Publication number | Publication date |
---|---|
CN115431264B (en) | 2024-07-09 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Bhattacharya et al. | Text2gestures: A transformer-based network for generating emotive body gestures for virtual agents | |
Argall et al. | A survey of robot learning from demonstration | |
Beer | Computational and Dlmamical Languages for Autonomous Agents | |
Clegg et al. | Learning to collaborate from simulation for robot-assisted dressing | |
Mochizuki et al. | Developmental human-robot imitation learning of drawing with a neuro dynamical system | |
Lebourque et al. | A complete system for the specification and the generation of sign language gestures | |
Luo et al. | A generalized robotic handwriting learning system based on dynamic movement primitives (dmps) | |
Dong et al. | Passive bimanual skills learning from demonstration with motion graph attention networks | |
Solis et al. | Reactive robot system using a haptic interface: an active interaction to transfer skills from the robot to unskilled persons | |
Zhang et al. | Learning robust point-to-point motions adversarially: A stochastic differential equation approach | |
CN115431264B (en) | Interactive motion control method and system with individual features | |
Guo et al. | Exploiting LSTM-RNNs and 3D skeleton features for hand gesture recognition | |
Zhou et al. | Modeling of endpoint feedback learning implemented through point-to-point learning control | |
Stubbe | Articulating novelty in science and art: The comparative technography of a robotic hand and a media art installation | |
Reiter et al. | Spacecraft detection avoidance maneuver optimization using reinforcement learning | |
Hosseini et al. | “Let There Be Intelligence!”-A Novel Cognitive Architecture for Teaching Assistant Social Robots | |
Ruiz-del-Solar et al. | Analyzing the human-robot interaction abilities of a general-purpose social robot in different naturalistic environments | |
Kaerlein | Social Robots Should Mediate, Not Replace, Social Interactions | |
Alemi | “Let There Be Intelligence!”-A Novel Cognitive Architecture for Teaching Assistant Social Robots | |
Cheng et al. | A framework of an agent planning with reinforcement learning for e-pet | |
Xu et al. | Robots Learn to Write via Human–Robot Interaction | |
Neff | Aesthetic exploration and refinement: A computational framework for expressive character animation | |
Weststeijn et al. | Painting as" Reall Performance" in Rembrandt's Studio | |
Murata et al. | Analysis of imitative interactions between humans and a robot with a neuro-dynamical system | |
Nemoto et al. | Design of Humanity by the Concept of Artificial Personalities |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |