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Web-Based Command Shaping of Cobra 600 Robot With a Swinging Load Timothy Chang, Member, IEEE, Puttiphong Jaroonsiriphan, Michael Bernhardt, and Paul Ludden
Abstract—This work focuses on the real-time control of a swinging load through the Internet. In particular, command shaping is applied to move a cable suspended load at the end point of an Adept Cobra 600 4-axis SCARA robot, with the objective of minimizing load swing. The first part of this paper discusses inverse kinematics, pendulum dynamics calculations, the corresponding shaping control algorithm, and the effects of transmission time delay. Standardized Internet interface via the DataSocket software in LabVIEW is then addressed in the second part. Simulation and experimental results confirm the feasibility of real time command shaping control through the Internet.
I. INTRODUCTION ITH the increase in bandwidth through high speed and dedicated data lines, web-based robot control is gaining a significant role in supporting collaborative research and industrial operations by providing a 24/7 access environment with real time information exchange. While the industry is beginning to embrace Internet control technology, full scale deployment of web-based robot control is still impeded by a number of factors such as • communication bandwidth; • connection reliability; • time delay; • interface and software standards; • security; • initial development costs. With the broad availability of high speed lines, bandwidth is becoming less inhibiting provided the control interfaces are appropriately designed. Connection reliability challenges both the network infrastructure as well as robustness of the control design [1]. Time delay remains a significant problem as the web traffic is at times unpredictable. Controllers not designed to handle time delay will introduce significant performance deterioration and even instability into the system [2]. Evolution of interface and software standards has been a long process. Earlier systems [3], [4] rely on custom software development, e.g., cgi/Perl, Java/C++, etc. Maintenance and upgrade of the codes become problematic. Furthermore, earlier systems lack real-time streaming capabilities due to the client side control privilege. The more recent implementations of the web
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Manuscript received September 29, 2004; revised October 5, 2005. T. Chang, P. Jaroonsiriphan, and P. Ludden are with the Department of Electrical & Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA (e-mail:
[email protected]). M. Bernhardt was with the Department of Electrical & Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA. He is now with the Institute of Automatic Control Engineering, Technical University of Munich, Munich, Germany. Digital Object Identifier 10.1109/TII.2005.864143
Fig. 1. Hardware set up showing the Cobra 600 with a swinging pendulum.
experiments are based on existing software platforms such as LabVIEW or Matlab. In [5] and [6], various web experiments are supported by the Wincon/Simulink combination package through TCP/IP protocol. In [7], distance experiments in process control and dynamics are made available via LabVIEW interface. In [9], monitoring of distributed processes are carried out on LabVIEW TCP/IP VI (Virtual Instrumentation) using the HTTP web server. In [10] and [11], web-based mobile robot controls are discussed. Further work remains to be done to establish an efficient, open architecture interface standard for real time control over the Internet [8]. This work addresses the design of command shaping for a swinging load where the command sequences are transmitted through the Internet. Effects of transmission time delay are assessed in terms of residual oscillation of the load. An open architecture web interface is also discussed, followed by experimental verifications on an Adept Cobra 600 system. II. HARDWARE DESCRIPTION AND ROBOT KINEMATICS The Adept Cobra 600 4-axis SCARA robot is shown in Fig. 1. The Cobra 600 has a reach of 600 mm in the horizontal (x-y) plane and a reach of 210 mm in the vertical (z) direction with a maximum payload of 5.5 kg. The ranges of motion for the , joint 2: , joint 3: joints are as follows: joint 1: 210 mm, joint 4: . Joint 1 is the joint connected directly to the base of the robot. Its motion is in the x-y plane. Joint 2 is the next link out attached to the end of joint 1. Its motion is
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Fig. 2. Model of Adept Cobra 600 robot with pendulum suspended perpendicular to the x-y plane.
also in the x-y plane. Joint 3 is located at the end of joint 2 and oriented perpendicular to joint 2. As indicated by the joint range of motion, the motion of joint 3 is purely up and down along the z-axis. Joint 4 is the rotation of the end effector to which a pendulum is attached. The experimental set up shown in Fig. 1 can be expressed in the model as shown in Fig. 2. The load is vertically suspended so that the natural from the plane at a distance of which is more frequency of the pendulum is about than 1 decade below the robot’s bandwidth. Therefore, the manipulator analysis can be simplified to focus on the dynamics of pendulum whose equation governing the motion of the pendulum is given by (1) where , , , , and are, respectively, swing angle of the pendulum, cable length of the pendulum, gravitational constant, mass of the load, and applied force. To execute a linear motion at the end point of the robot, only two degree-of-freedom using joint 1 and joint 2 of the robot, are required. The robot is powered and operated through the Adept MV-1060 controller. This controller consists of two separate towers, a PA-4 power amplifier chassis and a MV-10 Adept Windows controller chassis. The PA-4 power amplifier runs on 220 V 3-phase power. The MV-10 controller runs on 110 V single phase power. The MV-10 controller has internal memory with the V+ programming environment loaded on it as well as free space for storing program codes. A PC is connected to the MV-1060 via a high speed LAN. The PC standardizes the web interface requirements for modular connection to the main server. Refer to Fig. 2, Table I shows notations are used to describe the characteristics of the robot.
III. COMMAND SHAPING DESIGN FOR WEB-BASED SYSTEMS WITH TRANSMISSION TIME DELAY VARIATIONS Generally speaking, web-based control consists of two loops: an inner loop local to the robot controller and an outer loop carried over from the Internet. The inner loop is maintained for system stability, integrity against connection failure, and bandwidth conservation. The codes of the inner loop can be uploaded from the clients to the server then onto the robot controller. The outer loop may contain command and servo loops that are executed in the client sites. To mirror such dual-loop structure, control for the swinging pendulum comprises of a local feedback control which regulates the basic joint motions and a web-based control which enhances the performance of the system. In this work, the attention is focused on web-based feedforward control which provided point-to-point direction of the pendulum position. To suppress load swing, the method of input shaping is applied [13], [14] to eliminate or reduce the residual vibrations in the system responses by self-canceling oscillations, thereby improving dramatically the performance. A brief mathematical overview of the input shaping scheme [14], [15] is presented. For simplicity, a second order system (2) subject to an m-impulse excitation is considered:
(2) The unit impulse response of (2) is given as
(3) where is the impulse time and u(.) is the unit step function. Let be the response to impulse .
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TABLE I NOTATIONS OF ROBOT KINEMATICS
Then the total response is
Alternatively, (4)
where (9) (5)
or
Let (6) and
(10) (7)
The total response at settling time
can be written as
(8)
and terms, the By eliminating the residual vibration can, therefore, be expressed as (11), shown at the bottom of the page. and , . Now since also depends upon and to zero out the residual viIt is possible to solve for
(11)
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Fig. 3. Effects of transmission time delay variations on residual vibration for (a) ZV and (b) ZVD.
Fig. 4. Simulation model of pendulum with shaped command subjected to transmission time delay.
bration. In the case that derived [14] as
, the ZV (Zero Vibration) shaper
(12) and where For , the Zero Velocity & Derivative (ZVD) shaper is derived [14] as
(13) In general, the shaper is indirectly realized by convolving the impulses with the input command mathematically at the client site. After the convolution, the impulse weight and timing translate into amplitudes and time separation as given in (12) and can be trans(13). For web-based control, the amplitudes mitted accurately whereas the switch time is subject to propagation time delay. It is therefore recommended that the de-
sign incorporates the (known) nominal transmission time delay into the switch time and then assesses the effects of time delay variations about this nominal value using the residual vibration . For ZV and ZVD, the effects of transmission time delay variations on residual vibration are summarized in Fig. 3. As shown in Fig. 3, the ZV design has a higher sensitivity to transmission time delay particularly when the system damping . For 10%, residual vibration, the time is low delay variation is 6% about the nominal delay. The ZVD design, on the other hand, is more robust and can tolerate 20% delay time variations. This is; however, at the expense of a slower command cycle. Furthermore, in certain cases, the statistical nature of delay time variation may be known and can be modeled with a probability distribution. The pattern of variations can be incorporated into the shaper design to minimize the expected level of residual vibration [15]. To illustrate the effects of transmission time delay on shaper performance, a series of simulation studies have been performed with step command entering the shaper as shown in Fig. 4. The results for zero damping (the worst case) are plotted in Fig. 5. It is observed that the ZVD method is slower but more robust with respect to the variations about the nominal delay as indicated in Figs. 3 and 5. The choice of algorithm largely depends on the magnitude of transmission time delay variations, acceptable level of residual vibration, as well as speed of response. of the pendulum as the Consider now the swing angle oscillatory response which is to be kept close to zero as the end
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Fig. 5. Normalized outputs subjected to the effects of various transmission time delays incorporated into the switch time t of the shaped commands (a) ZV and (b) ZVD, where represents fractional transmission time delay variation about the nominal delay.
D
Fig. 6. Impulse shaper input applied to the system.
of joint 2 follows a linear trajectory shown in Fig. 2. A total of 4 switches are needed to execute a ZV shaper to complete the start is the impulse and stop operations as shown in Fig. 6, where , input causing the robot to reach half of maximum speed is the impulse input causing the robot to reach the maximum speed , is the impulse input causing the robot to reach , and impulse input causing half of maximum speed the robot to reach zero speed. The concept of input shaping applied to the robot experiment is shown in Fig. 7. , the robot accelerates from speed • Starting when impulse is applied to the system. The swing angle of the pendulum will . oscillate by , the robot accelerates from speed • At when the impulse is applied to the system. Then the swing angle of the pendulum will
as well. The oscillaoscillate by tions from both the impulse inputs are totally out-of-phase and thereby canceling each other. Therefore, the swing angle of the pendulum equals zero from the time that the second impulse is applied. , the robot decelerates from speed • At during the impulse application. Then the swing angle of the pendulum will oscillate by in the opposite direction. , the robot decelerates from • At with impulse applied to the system. speed Then the swing angle of the pendulum will oscillate by in the same direction of that of the previous step. The oscillations from both of the impulse inputs cancel each other; therefore, the swing angle of the pendulum equals to zero from the time that the fourth impulse is applied. , the swing angle of the pendulum equals to • At zero at all time. Cancellation of the oscillation waveform resulting from the input shaped commands is shown in Fig. 8. It is evident that load swing ceases after the pendulum is over the new position. Assuming zero damping for the pendulum and an oscillation , the ZV shaper veperiod of the pendulum of locity and position profile can be readily determined with time durations over the range of the total distance on the x-axis, of (duration of time for half of maximum speed after acceleration), (duration of time for maximum speed), and (duration of time for half speed after deceleration) as shown in Fig. 9(a). Fig. 9(b) shows pendulum base distance with respect to time . Finally the relationship between , and time can be obtained and is shown in Fig. 10(a) and (b). In practice, either one of the sequence shown in Figs. 9 or 10 can be transmitted. Now
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Fig. 7. Swing angle ( ) of pendulum at each period of time.
Fig. 8. Swing angle ( ) of pendulum under input shaping command.
since the MV10 controller readily handles inverse kinematics, the end effector velocity is used for the experiment. IV. REAL-TIME WEB CONNECTION This section describes the web interface necessary for the remote control of the Adept Cobra 600. It is the objective of this work to devise and implement an open architecture, webbased control system that possesses the following characteristics: efficient interactive/multi-user operations, machine independent (currently developed for the PC platform), secure operations, GUI compatible, bandwidth efficient with true real-time data streaming capabilities, low cost, user friendly interface, and global resource sharing.
In this work, web-based shaping control of an Adept Cobra 600 robot supported by LabVIEW/DataSocket is discussed with emphasis on the shaper design and web control implementation. For the present system there are two layers of interfaces, which are shown as a block diagram in Fig. 11: (A) Interface between the server and remote clients, and (B) Interface between the server and the Adept Cobra VME controller. These layers are now described. A. Interface Between the Server and Remote Clients The advantage of DataSocket application is to eliminate the need to write the complicated parsing code by automatically converting a streaming of live transferred data, regardless of
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Fig. 9. (a) Robot end point speed. (b) Position profile under command shaping control.
Fig. 10. (a) Joint angle versus t. (b) Joint angle versus t.
the data types used [12]. The client can control and monitor the robot motion in real time as long as the communication bandwidth is high enough. The client virtual instrumentation panel opened on a web browser is shown in Fig. 12. To conserve bandwidth, a mimic of the robot joints is created and animated by using robot joint data in both server and client sites. The animation eliminates the need for video transfer. B. Interface Between the Server and the Adept Cobra VME Controller There are three different user interface options for the Adept Cobra controllers. • An ASCII interface using a Wyse terminal (or equivalent)
• A GUI using the Adept VGB board, an SVGA monitor, a standard PC-style keyboard, and a serial pointing device. • A GUI using the AdeptWindows PC software running on a PC. The AdeptWindows PC Microsoft Windows based program allows full V+ programming and control of the robot from an IBM compatible personal computer. The server can be connected to the Adept Cobra VME controller using either a serial cable or an Ethernet link. TCP/IP is used for an interface between the server PC and the Cobra MV10 VME controller. A number of steps are required to interface the VME controller to the server PC: 1) Apply the correct port number and IP address of the controller. 2) Execute the corresponding V+ program to establish TCP/IP connection.
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Fig. 11. Block diagram of the robot experiment connection.
Fig. 12. Client panel control.
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Fig. 13. (a) Swing angle of pendulum subject to transmission time delay variations incorporated into switch time t . (b) The pendulum tip position with respect to time delay variations.
3) Transfer live data, which contains joint position control commands and speed of the robot to the controller. Interface Between a Server PC and Adept Cobra VME Controller by Using AdeptWindows PC Software: The AdeptWindows PC software allows an operator or administrator at the server PC site to upload, download, or edit the V+ programming into the Adept Cobra controller by specifying the IP address of the controller. The AdeptWindows PC software provides the server PC with a connection to the controller through the Internet and also provides the command window on the server PC. The robot control program is a V+ program that directly controls the Adept Cobra robot. Executable programs and command programs for controlling the Adept Cobra robot are created by using the V+ programming language on the server PC site. After these programs are loaded and stored in the Adept Cobra controller, an administrator who creates these programs can execute the programs through the Internet connection. After the program has already executed, the controller is definitely available for the robot controlling, then the LabVIEW program in the server PC can be executed. Interface Between a Server PC and Adept Cobra Controller by Using LabVIEW Program: A LabVIEW program which is located on the server PC is the program that interfaces to the Adept Cobra controller. TCP/IP is used for an interface between the server PC and the controller. The port number and an IP address of the controller have to be correctly specified. Right after the V+ program has been executed and the TCP/IP connection has been completed. Then, LabVIEW program will transfer live data which contains joint position control commands and the speed of the robot to the controller. The client LabVIEW program is also executed to synchronize with the LabVIEW program on the server site by sending the real-time data to the server site to execute and manipulate the robot controller. The remote users connect to the robot experiment via a standard web browser enhanced with a LabVIEW plug-in. As shown in Fig. 12, two-dimensional (2-D) animations are visually displayed robot joints. The first animation shows an overhead view
of the robot allowing the user to see the position of joints 1 and 2. The second animation is for joints 3 and 4. This animation is of a constant perspective. To the left of the animations, the dynamic numerical joint data is displayed. This allows the user to ascertain exact positions of the robot that cannot be directly obtained from the animations if it is needed. Above this information is a section whereby the user can remotely control the robot either interactively (for training) or by batched (for command shaping). V. SIMULATION AND EXPERIMENT RESULTS To verify the designs, the model shown in Fig. 4 is simulated with various transmission time delay variations. Fig. 13(a) shows the swing angle of the pendulum whose input command as shown in Fig. 9(a) is applied and subject to transmission time delay variations that are incorporated into switch time of the shaper. From the simulation, the pendulum tip position encountering different the transmission time delay variations is displayed in Fig. 13(b). It is observed that the residual vibration deteriorates with increased transmission time delay variations as discussed in Section III. A graph of shaped command pendulum experimental response is shown in Fig. 14. The load position in the x-direction is measured by a video camera. It is noted that the experimental trajectory agrees well with the theoretical prediction. The small amount of residual vibration is due to mismatches on the damping coefficients and transmission time delay variation. It should be mentioned that the residual vibration could manifest itself as a 2-D oscillation in the x-y plane depending on machine precision, modeling error, and transmission time delay variations. To improve parameter matching by using an additional switch in the shaper design (ZVD), which is more robust, will alleviate this problem by lowering the residual vibration. However, the transmission time delay still has an effect on the output considerably. The more time delay is applied, the higher residual vibration is produced.
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sual display of robot in animation (Fig. 12) or video streaming. This way, students/schools can experiment with advanced hardware without incurring expensive overhead costs. This is especially significant for under-developed/economic disadvantaged areas. It is envisioned that future laboratories may consists of a series of decentralized facilities that are brought together by web access technologies. VII. CONCLUSIONS
Fig. 14. Experimental pendulum tip position.
VI. OTHER WEB-RELATED CONSIDERATIONS As the web interface discussed in this paper is based on the LabVIEW/DataSocket platform, a number of limiting factors exist. They are described as follows. Single Client Control Synchronization: The robot experiment is controlled by a single client at a time. With multiple client access, the remote panel connection manager configuration will assign sole control to the first log-in client. The other clients are able to monitor the robot experiment online and are in queue for taking over the control of the robot experiment on a first come first serve basis until they are assigned as the controlling user. Limited Data Bandwidth: Depending the mode of access (LAN, DSL, dial-up, etc.), the transmission bandwidth can vary significantly. Therefore, the web interface design and control algorithm must be efficient to accommodate the slowest clients. For lines with high transmission time delay uncertainty, the ZVD algorithm should be considered [see (13) and Figs. 3(b) and 5(b)]. Network Firewall and VPN: The standard firewall set up provides critical network security but also inadvertently limits user write operations. To overcome the firewall and access to the robot experiment, the remote client may need virtual private network (VPN). The remote clients also must have authorization from the organization whose network the robot system is connected to. The connection with VPN allows the remote clients to control the robot experiment as if the clients are working on the same LAN which the robot experiment connects to within the firewall of the organization. Learning Modes: Besides direct industrial applications, the web-based method described in this paper can also be used for education/collaborative research and global resource sharing in following modes: — intra/inter-campus; — inter-university; — K-12/university; — international The users remotely connect to the robot experiment via web interface and then receive robot kinematics information via a vi-
Application of command shaping to the control of a swinging load via the internet is addressed in this paper. Two aspects are considered: designing a shaper with uncertain transmission time delay and implementation/verification of the design on a Cobra 600 robot. Once the load dynamics and robot inverse kinematics have been calculated, a command shaper is designed and implemented. Robustness of the ZV and the ZVD shapers are assessed. It is observed that while the ZVD is slower, it is significantly more tolerant to transmission time delays. LabVIEW programs are then created to provide an open architecture interface between the server and the remote clients while the DataSocket Server Manager controls real time data transfer, data queue, and system security. Experimental results confirm the viability of real-time control through the internet in conjunction with command shaping. ACKNOWLEDGMENT The authors wish to express their gratitude to Adept Technologies, Inc. for the donation of an Adept Cobra 600 robot and technical support. REFERENCES [1] R. J. Veillettea, J. V. Medanic, and W. R. Perkins, “Design of reliable control systems,” IEEE Trans. Automat. Control, vol. 37, pp. 290–304, 1992. [2] T. N. Chang and E. J. Davison, “The decentralized robust stabilization and regulation problem subject to gain and phase perturbation,” in Proc. American Control Conf., 2001, vol. 5, pp. 4052–4057. [3] B. Aktan, C. A. Bohus, L. A. Crowl, and M. H. Shor, “Distance learning applied to control engineering laboratories,” IEEE Trans. Educ., vol. 39, no. 3, pp. 320–326, Aug. 1996. [4] H. Shen, Z. Xu, V. Kristiansen, O. Strom, and M. Shur, “Conducting laboratory experiments over the internet,” IEEE Trans. Educ., vol. 42, no. 3, pp. 180–185, Aug. 1999. [5] T. F. Junge and C. Schmid, “Web-based remote experimentation using a laboratory-scale optical tracker,” in Proc. Amer. Control Conf., Chicago, IL, Jun. 28–30, 2000, vol. 4, pp. 2951–2954. [6] C. Schmid and A. Ali, “Web-based system for control engineering education,” in Proc. American Control Conf., Chicago, IL, Jun. 28–30, 2000, vol. 5, pp. 3463–3467. [7] J. Henry, “Running laboratory experiments via the world wide web,” in 1998 Nat. Meeting ASEE, Seattle, WA. [8] T. N. Chang and D. C. Hung, “Web-based distance experiments: design and implementation,” in Proc. Int. Conf. Engineering Education, Taiwan, R.O.C., Aug. 14–18, 2000. [9] K. K. Tan, T. H. Lee, and C. Y. Soh, “Remotely operated experiment for mechatronics: monitoring of DCS on the internet,” in IEEE/ASME Int. Conf. Advanced Intelligent Mechatronics, AIM, Como, Jul. 8–12, 2001, vol. 2, pp. 1106–1111. [10] Q. Chen, H. Geng, and P. Y. Woo, “Research on and pure java realization of a web-based mobile robot system,” in Proc. 2003 Amer. Control Conf., June 2003, pp. 615–620. [11] D. Schulz, W. Burgard, D. Fox, S. Thrun, and A. B. Cremers, “Web interfaces for mobile robots in public places,” IEEE Robot. Automat. Mag., vol. 7, no. 1, pp. 48–56, Mar. 2000.
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[12] T. N. Chang, P. Jaroonsiriphan, and X. Sun, “Integrating nanotechnology into undergraduate experience. A web-based approach,” Int. J. Eng. Educ., vol. 18, pp. 557–565, Nov. 5, 2002. [13] W. Singhose, L. Porter, M. Kenison, and E. Kriikku, “Effect of hoisting on the input shaping control of gantry cranes,” Control Eng. Pract., vol. 8, pp. 1159–1165. [14] N. Singer and W. Seering, “Preshaping command inputs to reduce system vibration,” ASME J. Dynam. Syst., Meas. Contr., vol. 112, no. 1, pp. 76–82, 1990. [15] T. N. Chang, E. Hou, and K. Godbole, “Optimal input shaper design for high speed robotic workcells,” J. Vibr. Control, vol. 9, no. 12, pp. 1359–1376, Dec. 2003. Timothy Chang (M’78) received the Ph.D. degree in electrical engineering from the University of Toronto, Toronto, ON, Canada. He is an Associate Professor at the Department of Electrical & Computer Engineering and Coordinator of the Intelligent Systems Area, New Jersey Institute of Technology (NJIT), Newark. Prior to joining NJIT in 1991, he was a Senior Research Specialist and Program Manager at Kearfott Guidance and Navigation Corporation , Little Falls, NJ, in charge of the Doppler mirror ring laser gyroscope program. He holds four patents with three patents pending. His areas of interest include: ultra-high precision systems, robotics, embedded real time systems, decentralized control systems, traffic systems, microarray systems, and personalized weapons technology. His research has been supported by the National Science Foundation, National Institute of Standards and Technology, National Institute of Justice, Department of Transportation, U.S. Army ARDEC, New Jersey Commission on Science and Technology, and New Jersey Commission on Higher Education. Dr. Chang is the recipient of six education awards and he was conferred the title of “Master Teacher” at NJIT in 2003. He is also the Chairman of the North Jersey IEEE Control Systems Chapter and Advisor to the IEEE student branch at NJIT. Puttiphong Jaroonsiriphan received his B.S. degree in electrical engineering from Kasetsart University (KU), Bangkok, Thailand, in 1994, and the M.S. and Ph.D. degrees in electrical engineering from New Jersey Institute of Technology (NJIT), Newark, NJ, in 1998 and 2006, respectively. After his graduation in 1994, he worked for Siam Iron and Steel Co., Ltd., Thailand, as a Design and Control Engineer, in charge of the revamp of a ladle
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car project for increasing efficiency of the plant line. After he received the M.S. degree from NJIT in 1998, he worked for Phoenix Lighting, Inc., which collaborated with other lighting companies to upgrade lighting for shopping malls and government buildings. During his Ph.D. studies, he worked as a Teaching Assistant for the Department of Electrical and Computer Engineering at NJIT. Dr. Jaroonsiriphan received an Honorable Mention Award in the 2003 NJIT Excellence in Teaching by a Teaching Assistant category. He was also nominated for an NJIT Excellence in Teaching Award in 2004 and 2005.
Michael Bernhardt received the B.Sc. and Dipl.-Ing. degrees in electrical engineering from the Technical University of Munich (TUM), Germany, in 2002 and 2004, respectively. During his studies he spent a semester followed by a research internship at the New Jersey Institute of Technology (NJIT), Newark. He spent another year at the Swiss Federal Institute of Technology (ETH), Zurich, to work on his diploma thesis and as a Research Assistant in the area of rehabilitation robotics. He is currently pursuing the Ph.D. degree student and is a Research Assistant at the Institute of Automatic Control Engineering at the TUM. His research interest is rehabilitation engineering, especially controlled induction of finger movements of hemiplegic stroke patients with repetitive peripheral magnetic stimulation.
Paul Ludden received the B.S. and M.S. degrees in electrical engineering from the New Jersey Institute of Technology (NJIT), Newark, in 2002 and 2004. Upon receiving the M.S. degree, he entered the aerospace and defense industry working for BAE Systems, Rockville, MD, where he is currently an Avionics Engineer. He is also currently an Adjunct Professor of automatic control systems at NJIT.
