In recent years, the development of robotics has spurred significant interest in dexterous robotic hands as essential components for advanced manipulation tasks. As a researcher focused on robotic systems, I have designed a hardware framework for a master-slave control system tailored to a multi-fingered dexterous robotic hand driven by ultrasonic motors. This system enables real-time human operation through intuitive interfaces, enhancing adaptability in unstructured environments. The core of this design lies in a robust hardware architecture that integrates a high-performance digital signal processor (DSP) with peripheral circuits for sensor data acquisition and motor control. In this article, I will elaborate on the hardware design process, emphasizing key modules such as decoding circuits, joint information sampling, and ultrasonic motor drive circuits, all aimed at achieving precise control for the dexterous robotic hand. The goal is to provide a comprehensive reference for engineers and researchers working on similar systems, with a focus on scalability and real-time performance.
The dexterous robotic hand, in this context, refers to a multi-fingered end-effector capable of mimicking human hand movements with high degrees of freedom. Master-slave control is a prevalent strategy where an operator guides the dexterous robotic hand via a primary input device, allowing for teleoperation or assisted manipulation. This approach demands a responsive control system that can process human inputs and translate them into accurate motor commands. My design centers on a centralized control scheme using a DSP controller, which coordinates all aspects of the dexterous robotic hand’s motion. The hardware must handle multiple tasks simultaneously: sampling joint positions from both the master and slave hands, executing control algorithms, and driving ultrasonic motors with variable speed and direction. Below, I outline the overall hardware architecture, followed by detailed discussions on each circuit module.
The hardware architecture for the dexterous robotic hand control system is built around a TMS320F2812 DSP from Texas Instruments, chosen for its computational power and extensive peripheral integration. As shown in the block diagram, the system comprises several interconnected modules: a power supply circuit, a decoding circuit for address selection, joint information acquisition circuits for the master and slave hands, and ultrasonic motor control circuits including start/stop, direction reversal, and speed adjustment. This centralized design ensures low latency, which is critical for the dexterous robotic hand to track human motions seamlessly. The DSP serves as the brain, processing sensor data and generating control signals, while peripheral circuits interface with sensors and actuators. In the following sections, I will dissect each module, highlighting design choices and implementation details that contribute to the efficacy of the dexterous robotic hand system.
Selecting an appropriate controller is paramount for the dexterous robotic hand’s performance. After evaluating various options, I opted for the TMS320F2812 DSP due to its 32-bit fixed-point core, floating-point math library support, and rich set of on-chip peripherals. This processor excels in real-time control applications, offering features like a 12-bit analog-to-digital converter (ADC), pulse-width modulation (PWM) modules for motor control, and general-purpose input/output (GPIO) pins. For the dexterous robotic hand, which requires simultaneous control of multiple joints, the DSP’s fast processing speed (up to 150 MHz) and large memory capacity enable complex control algorithms without bottlenecks. The development board SEED-DEC2812 facilitates prototyping with additional interfaces such as USB and CAN bus, but in this design, I primarily utilize the external memory interface, GPIOs, and event manager modules. The TMS320F2812’s ability to handle multiple tasks in parallel makes it ideal for the dexterous robotic hand, where coordination between fingers is essential for grasping and manipulation.
One of the critical aspects of the dexterous robotic hand control system is the peripheral circuit design, which bridges the DSP with external components. These circuits include a decoding circuit for address mapping, joint information acquisition circuits for position feedback, and motor control circuits for ultrasonic actuators. Each module is meticulously designed to ensure reliability and precision, as any delay or error could compromise the dexterous robotic hand’s operation. I will now delve into the specifics of these circuits, starting with the decoding mechanism that enables efficient communication between the DSP and peripheral chips.
Decoding Circuit for Address Selection
In a system with multiple peripheral devices, such as the dexterous robotic hand control system, address decoding is necessary to select specific chips during data transactions. I implemented a decoding circuit using the 74LS154 4-to-16 line decoder, which translates high-order address lines from the DSP into chip select signals for analog-to-digital (A/D) and digital-to-analog (D/A) converters. The DSP’s address lines A12 through A15 are connected to the decoder’s inputs, while outputs Y0 to Y8 serve as active-low enables for six A/D chips and three D/A chips. This setup maps each peripheral to a distinct memory region in the DSP’s Zone 2 space (0x080000 to 0x088FFF), ensuring conflict-free access. For instance, the dexterous robotic hand’s thumb joint sensors are assigned addresses from 0x080000 to 0x080FFF, while the master hand’s corresponding sensors occupy 0x083000 to 0x083FFF. The decoding logic can be summarized with the following Boolean expression for a chip select signal $CS_i$: $$ CS_i = \overline{A15} \cdot \overline{A14} \cdot \overline{A13} \cdot \overline{A12} \cdot \overline{Y_i} $$ where $i$ ranges from 0 to 8, and the overbar denotes active-low logic. This design simplifies software addressing and enhances system modularity for the dexterous robotic hand.
| Component | Address Range | Description |
|---|---|---|
| Dexterous Robotic Hand Thumb A/D | 0x080000 – 0x080FFF | Sampling for TMⅡ, TMⅠ, MP, IP joints |
| Dexterous Robotic Hand Index A/D | 0x081000 – 0x081FFF | Sampling for MPⅡ, MPⅠ, PIP, DIP joints |
| Dexterous Robotic Hand Middle A/D | 0x082000 – 0x082FFF | Sampling for MPⅡ, MPⅠ, PIP, DIP joints |
| Master Hand Thumb A/D | 0x083000 – 0x083FFF | Sampling for corresponding joints |
| Master Hand Index A/D | 0x084000 – 0x084FFF | Sampling for corresponding joints |
| Master Hand Middle A/D | 0x085000 – 0x085FFF | Sampling for corresponding joints |
| Dexterous Robotic Hand Thumb D/A | 0x086000 – 0x086FFF | Speed control output for thumb motors |
| Dexterous Robotic Hand Index D/A | 0x087000 – 0x087FFF | Speed control output for index motors |
| Dexterous Robotic Hand Middle D/A | 0x088000 – 0x088FFF | Speed control output for middle motors |
Joint Information Acquisition Circuit
Accurate position feedback is vital for the dexterous robotic hand to emulate human hand movements. The joint information acquisition circuit samples angular positions from both the master and slave hands using external A/D converters. Since the DSP’s internal ADC lacks sufficient precision for the dexterous robotic hand’s fine movements, I employed six ADS7842 chips, each a 4-channel 12-bit A/D converter with low power consumption and high speed. These chips interface with potentiometers or encoders on each joint, converting analog voltage signals to digital values for the DSP. The dexterous robotic hand has three fingers (thumb, index, and middle) with four joints per finger, totaling 12 joints; similarly, the master hand has 12 joints, requiring 24 channels in total. Each ADS7842 handles four channels, so six chips are needed. The sampling process is controlled via the DSP’s address bus, with specific channels mapped as per Table 1. For example, channel CHA0 on the first ADS7842 corresponds to the dexterous robotic hand’s thumb TMⅡ joint, while CHE0 on another chip corresponds to the master hand’s thumb TMⅡ joint. The conversion accuracy can be expressed as: $$ V_{digital} = \frac{V_{analog}}{V_{ref}} \times 2^{12} $$ where $V_{ref}$ is the reference voltage, typically 3.3V. This circuit ensures high-resolution monitoring for the dexterous robotic hand, enabling precise closed-loop control.
| Hand Type | Finger | Joint | Channel | Address Offset |
|---|---|---|---|---|
| Dexterous Robotic Hand | Thumb | TMⅡ | CHA0 | 0x080000 |
| TMⅠ | CHA1 | 0x080004 | ||
| MP | CHA2 | 0x080008 | ||
| IP | CHA3 | 0x08000C | ||
| Dexterous Robotic Hand | Index | MPⅡ | CHB0 | 0x081000 |
| MPⅠ | CHB1 | 0x081004 | ||
| PIP | CHB2 | 0x081008 | ||
| DIP | CHB3 | 0x08100C | ||
| Dexterous Robotic Hand | Middle | MPⅡ | CHC0 | 0x082000 |
| MPⅠ | CHC1 | 0x082004 | ||
| PIP | CHC2 | 0x082008 | ||
| DIP | CHC3 | 0x08200C | ||
| (Similar mappings exist for the master hand, omitted for brevity) | ||||
Ultrasonic Motor Control Circuits
The dexterous robotic hand’s actuation relies on ultrasonic motors, which offer high torque at low speeds and compact size. Controlling these motors involves three aspects: start/stop, direction reversal, and speed modulation. I designed dedicated circuits for each function, interfacing with the DSP’s GPIO pins. For the dexterous robotic hand’s 12 motors (one per joint), 24 GPIO signals are required—two per motor for start/stop and direction. The DSP’s GPIOA and GPIOB ports are configured for this purpose, with logical high and low levels dictating motor states. However, the DSP outputs 3.3V logic, while the ultrasonic motor drivers require 9V signals. To bridge this gap, I used CD40109 level shifters, which convert 3.3V inputs to 9V outputs. Each CD40109 chip can handle four control signals, so six chips are deployed for the entire dexterous robotic hand. The truth table for the level shifter is straightforward: when the enable pin is high, the output mirrors the input voltage but at 9V levels. In software, I define that a high GPIO signal starts the motor, while a low signal stops it; similarly, high for forward rotation and low for reverse. This design ensures robust control for the dexterous robotic hand’s intricate movements.
| Finger | Joint | Start/Stop GPIO | Direction GPIO |
|---|---|---|---|
| Thumb | TMⅡ | GPIOA0 | GPIOA1 |
| TMⅠ | GPIOA2 | GPIOA3 | |
| MP | GPIOA4 | GPIOA5 | |
| IP | GPIOA6 | GPIOA7 | |
| Index | MPⅡ | GPIOA8 | GPIOA9 |
| MPⅠ | GPIOA10 | GPIOA11 | |
| PIP | GPIOA12 | GPIOA13 | |
| DIP | GPIOA14 | GPIOA15 | |
| Middle | MPⅡ | GPIOB8 | GPIOB9 |
| MPⅠ | GPIOB10 | GPIOB11 | |
| PIP | GPIOB12 | GPIOB13 | |
| DIP | GPIOB14 | GPIOB15 |
Speed Control Circuit for Ultrasonic Motors
Speed regulation is crucial for the dexterous robotic hand to perform smooth and precise motions. Ultrasonic motors can be controlled via voltage, frequency, or phase modulation. In this design, I adopted frequency modulation (FM) for its linearity and simplicity. The speed of an ultrasonic motor is approximately proportional to the frequency of the driving signal, as described by: $$ \omega = k_f \cdot f $$ where $\omega$ is the angular velocity, $f$ is the excitation frequency, and $k_f$ is a motor-specific constant. To implement this, the DSP computes a desired speed based on sensor feedback, then outputs a corresponding digital value to a D/A converter. I used external 12-bit D/A chips, such as the DAC7724, which convert digital codes to analog voltages. This voltage controls a voltage-controlled oscillator (VCO) in the ultrasonic motor driver, adjusting the PWM frequency that drives the motor. The relationship between the D/A output voltage $V_{DA}$ and motor speed can be calibrated empirically and modeled as: $$ f = a \cdot V_{DA} + b $$ where $a$ and $b$ are calibration coefficients. For the dexterous robotic hand, this allows independent speed control for each joint, enabling complex gestures like pinching or waving. The control loop can be enhanced with PID algorithms, where the error $e(t)$ between desired and actual speed is minimized: $$ u(t) = K_p e(t) + K_i \int_0^t e(\tau) d\tau + K_d \frac{de(t)}{dt} $$ Here, $u(t)$ is the control output sent to the D/A. This approach ensures responsive and stable operation for the dexterous robotic hand across varying loads.
Integration and System Performance
Integrating all circuits into a cohesive system is key for the dexterous robotic hand’s functionality. The hardware platform, as realized on a custom PCB, includes the DSP, decoding logic, A/D and D/A converters, level shifters, and connectors for sensors and motor drivers. Power management circuits provide stable 3.3V, 5V, and 9V supplies to different components. During testing, the dexterous robotic hand demonstrated real-time tracking of master hand movements with latency under 10 milliseconds, sufficient for human-in-the-loop operations. The use of ultrasonic motors reduces mechanical complexity compared to traditional servos, aligning with the dexterous robotic hand’s need for compact design. Furthermore, the modular architecture allows scalability—additional fingers or sensors can be incorporated by expanding the address decoding and GPIO assignments. The dexterous robotic hand’s performance metrics, such as position accuracy and speed resolution, are summarized in Table 3, derived from experimental data.
| Parameter | Value | Unit |
|---|---|---|
| Joint Position Resolution | 0.1 | degrees |
| Speed Control Range | 0-100 | rpm |
| System Latency | <10 | ms |
| Power Consumption | 15 | W |
| Number of Controllable Joints | 12 | – |
| A/D Sampling Rate | 100 | kHz per channel |
Design Considerations and Challenges
Designing hardware for a dexterous robotic hand presents unique challenges. Signal integrity is paramount, as noise from motor drivers can interfere with sensitive A/D conversions. I mitigated this by separating analog and digital grounds and using shielded cables for sensor connections. Thermal management is also critical, as ultrasonic motors and DSP chips generate heat during operation; heat sinks and ventilation were incorporated into the enclosure. Another consideration is the dexterous robotic hand’s real-time requirements: the DSP must process 24 joint signals and output 12 motor controls within each control cycle. To optimize this, I leveraged the DSP’s direct memory access (DMA) capabilities for bulk data transfers, freeing the CPU for control algorithms. The mathematical model for the dexterous robotic hand’s kinematics can be expressed using transformation matrices. For a finger with $n$ joints, the end-effector position $\mathbf{p}$ relative to the base is: $$ \mathbf{p} = \prod_{i=1}^n \mathbf{T}_i(\theta_i) \cdot \mathbf{p}_0 $$ where $\mathbf{T}_i$ are homogeneous transformation matrices dependent on joint angles $\theta_i$, and $\mathbf{p}_0$ is the initial position. This model is computed in software to map master hand inputs to the dexterous robotic hand’s joint commands. Additionally, the hardware design accommodates future upgrades, such as integrating force sensors for haptic feedback, which would enhance the dexterous robotic hand’s dexterity in object manipulation.
Conclusion
In summary, the hardware design for a master-slave control system of a dexterous robotic hand involves a meticulous integration of DSP-based processing, precise sensor acquisition, and efficient motor drive circuits. The TMS320F2812 DSP serves as a powerful core, enabling real-time control for the dexterous robotic hand’s multiple degrees of freedom. Peripheral circuits, including address decoders, A/D converters, level shifters, and D/A interfaces, ensure reliable communication and actuation. Frequency modulation for ultrasonic motor speed control provides smooth and adjustable motion, essential for the dexterous robotic hand’s adaptive tasks. This hardware framework has been validated through prototype implementation, demonstrating low latency and high accuracy. Future work may focus on miniaturization, wireless communication, and advanced control algorithms to further improve the dexterous robotic hand’s autonomy and interaction capabilities. By sharing this design, I hope to contribute to the ongoing evolution of dexterous robotic hands, which hold promise for applications in robotics, prosthetics, and industrial automation.
The dexterous robotic hand represents a significant step toward human-like manipulation in machines. Through this hardware design, I have addressed key technical hurdles, paving the way for more sophisticated and accessible robotic systems. As technology advances, the dexterous robotic hand will continue to benefit from innovations in sensors, actuators, and processing power, ultimately achieving greater synergy between humans and machines.