🦀Robotics and Bioinspired Systems Unit 3 – Sensors and Actuators in Robotics

Key Concepts and Terminology

• Sensors detect and measure physical quantities (temperature, light, sound) and convert them into electrical signals for processing
• Actuators convert electrical signals into physical actions (motion, force) to interact with the environment
• Transducers encompass both sensors and actuators by converting energy between different forms
• Proprioception refers to a robot's ability to sense its own internal states (joint angles, motor speeds)
• Exteroception involves sensing the external environment (vision, touch, sound)
• Feedback loops enable robots to adjust their actions based on sensory input to achieve desired outcomes
• Bioinspiration draws design principles from biological systems to enhance robotic capabilities (insect-inspired navigation, gecko-inspired adhesion)

Types of Sensors in Robotics

• Vision sensors (cameras) capture visual information for object recognition, navigation, and interaction
  • Monocular cameras provide 2D images while stereo cameras enable depth perception
  • Event-based cameras detect changes in brightness for fast, low-latency sensing
• Tactile sensors measure contact forces and pressure for grasping, manipulation, and surface characterization
  • Resistive sensors change resistance under applied pressure
  • Capacitive sensors detect proximity and touch through changes in capacitance
• Inertial Measurement Units (IMUs) combine accelerometers and gyroscopes to measure linear acceleration and angular velocity for estimating pose and motion
• Encoders measure the angular position and velocity of motors for precise control and odometry
• Range sensors (ultrasonic, infrared, LiDAR) determine the distance to objects for obstacle avoidance and mapping
• Force/torque sensors measure the forces and moments applied to a robot's end-effector for force control and interaction

Actuator Fundamentals

• Electric motors convert electrical energy into mechanical energy for generating motion
  • DC motors provide high torque and are easily controlled using PWM signals
  • Stepper motors enable precise positioning without feedback
  • Servo motors integrate position feedback for accurate angular control
• Pneumatic actuators use compressed air to generate linear or rotary motion
  • Offer high power-to-weight ratio and compliance but require air compressors
• Hydraulic actuators use pressurized fluids for high-force applications (industrial robots, heavy machinery)
• Shape Memory Alloys (SMAs) deform when heated and return to their original shape when cooled, enabling compact, lightweight actuation
• Piezoelectric actuators expand or contract under applied voltage for precise, high-frequency movements (micro-positioning, vibration control)
• Soft actuators (pneumatic artificial muscles, electroactive polymers) provide compliant, flexible actuation for bioinspired and wearable robotics

Sensor-Actuator Integration

• Sensor fusion combines data from multiple sensors to improve accuracy, robustness, and reliability
  • Kalman filters probabilistically estimate states by fusing sensor measurements and model predictions
• Actuator control involves mapping desired actions to appropriate actuator commands
  • PID controllers minimize the error between desired and actual states through proportional, integral, and derivative terms
• Sensor-based control uses sensory feedback to adapt actuator commands in real-time
  • Visual servoing controls robot motion based on visual features
  • Force control adjusts actuator outputs based on force/torque sensor readings
• Embedded systems (microcontrollers, FPGAs) enable real-time processing and control of sensors and actuators
• Communication protocols (I2C, SPI, CAN) facilitate data exchange between sensors, actuators, and control systems

Bioinspired Sensing Mechanisms

• Insect-inspired compound eyes offer wide field of view and fast motion detection for navigating in dynamic environments
• Bat-inspired echolocation uses ultrasonic pulses and echoes for obstacle avoidance and prey localization
• Snake-inspired thermal sensing enables detection of warm objects (prey, humans) in low-light conditions
• Mammalian-inspired whisker sensors provide tactile feedback for object recognition and texture discrimination
• Octopus-inspired distributed tactile sensing enables adaptive grasping and manipulation
• Fish-inspired lateral line sensors detect water flow and pressure changes for underwater navigation and obstacle avoidance
• Human-inspired multimodal sensing combines vision, touch, and proprioception for dexterous manipulation and interaction

Control Systems and Feedback Loops

• Open-loop control applies pre-determined actuator commands without sensory feedback
  • Suitable for simple, predictable tasks but vulnerable to disturbances and uncertainties
• Closed-loop control uses sensory feedback to continuously adjust actuator commands based on the difference between desired and actual states
  • Enables adaptation to changing conditions and rejection of disturbances
• Proportional-Integral-Derivative (PID) control is a widely used feedback control scheme
  • Proportional term provides corrective action proportional to the error
  • Integral term eliminates steady-state error by accumulating past errors
  • Derivative term improves stability by anticipating future errors
• Adaptive control adjusts controller parameters in real-time to handle varying system dynamics and uncertainties
• Optimal control determines control inputs that minimize a cost function (energy consumption, time) while satisfying constraints
• Robust control maintains stability and performance in the presence of modeling errors and external disturbances

Applications in Modern Robotics

• Industrial robots use sensors and actuators for precise, repetitive tasks (welding, painting, assembly)
  • Force/torque sensing enables compliant manipulation and human-robot collaboration
• Autonomous vehicles rely on a suite of sensors (cameras, LiDAR, radar) and actuators (steering, braking, throttle) for perception, planning, and control
  • Sensor fusion and feedback control ensure safe, reliable navigation in complex environments
• Medical robots employ high-precision sensors and actuators for minimally invasive surgery and rehabilitation
  • Haptic feedback provides surgeons with tactile sensation during teleoperated procedures
• Humanoid robots integrate bioinspired sensing and actuation for human-like manipulation, locomotion, and interaction
  • Tactile sensors and dexterous hands enable grasping and manipulation of diverse objects
• Soft robots use compliant sensors and actuators for adaptability, safety, and bioinspired locomotion
  • Soft strain sensors and pneumatic actuators enable shape-changing and conformable structures
• Wearable robots (exoskeletons, prosthetics) augment human capabilities and assist individuals with mobility impairments
  • EMG sensors and torque-controlled actuators provide intuitive, responsive assistance

Challenges and Future Developments

• Sensor miniaturization and integration for compact, lightweight, and power-efficient sensing in small-scale robots
• Development of high-bandwidth, low-latency, and energy-efficient actuators for dynamic, agile movements
• Seamless integration of soft and rigid components for hybrid robots with the benefits of both compliance and precision
• Adaptive, learning-based control algorithms that can handle complex, unstructured environments and improve over time
• Bioinspired sensing and actuation principles for enhanced robustness, efficiency, and versatility
  • Insect-inspired resilience, mammalian-inspired energy efficiency, octopus-inspired adaptability
• Neuromorphic sensing and computing for low-power, real-time processing of sensory data
• Explainable AI and interpretable control for transparent, trustworthy decision-making in autonomous robots
• Ethical considerations and safety measures for responsible deployment of robots in society