Robotic Systems Flashcards
2 social & ethical implications of using telerobotics in healthcare
Legal liabilities - who to blame when malpractice occurs
Security of data when medical records pass through different hands/across digital platforms
Workspace
area containing all the points an end effector can reach
Forward dynamics
calculate joint trajectories, velocities & accelerations from known torque/forces from actuators at joints
Inverse dynamics
calculate forces/torques from known joint motion
path planning
mapping sequence of moves from start to end point for efficient movement & to avoid obstacles (geometry & environment of robot)
Trajectory
Specifies velocity, acceleration & timing of movement along planned path (accounts for dynamics & kinematics of robot)
Why include time history of position, velocity & acceleration of a robot? (4 points)
Achieve balance between:
- Operational efficiency (optimise velocity & acceleration for quickest & most energy-efficient path while respecting mechanical limits of manipulator)
- Precision (precisely control velocity & acceleration for smooth, repeatable movement)
- Safety (comply with physical & operational constraints e.g. max allowable velocity & acceleration, avoid abrupt movements that would endanger human operators/delicate parts in robot’s environment)
- Maintenance (deviations from norm indicate potential issues > improve lifespan & reliability of robot)
Joint (configuration) space: A&D, application
A - Smoother motion (planned path based on joint angles, directly controlling each joint’s movement) > maintains mechanical integrity & reduces wear on robot
D - lack of environmental awareness (less direct control over end-effector’s interaction with environment, doesn’t account for obstacles/specific requirements of task environment) > issues with collision avoidance
- manufacturing & assembly e.g. automotive assembly lines like screw driving/parts insertion (precise repeatable movements, consistent operation of robot’s joints where environmental interaction is minimal & controlled)
Task (Cartesian) space:
A&D, Application
A: Direct control of end-effector’s position & orientation (navigate complex paths & interact with objects in the environment) > high precision & specific interactions with objects
D: Complex computations (solve inverse kinematics at each point of trajectory > computation intensive) > slow operation but real-time applications may require rapid responses
- robotic surgery (precise control of surgical instruments’ positions & orientations is crucial to safety & effectively performing procedures on patients) > direct manipulation of end-effector to patient’s anatomy
Robot singularity
Reduced mobility, losing a DOF > large joint velocities are needed to cause robot’s end-effector to move at small velocities in cartesian space/robot cannot move any further in a specific direction > wear & tear
When is a robot in a singular condition?
Jacobian matrix doesn’t have an inverse (sine theta2 = 0) or determinant = 0
What is the Denavit-Hartenberg approach for and what are the 4 parameters?
assign coordinate frames to each joint to determine forward kinematic equations of a manipulator
L6, slide 16-19
What are the 2 assumptions on axes directions for the D-H parameters to exist & have unique values? (Sketch diagram to illustrate)
Axis xi perpendicular to axis zi-1
Axis xi intersects axis zi-1
L6 slide 15
Most important type of robot in manufacturing sector in Industry 4.0 & its features
Collaborative/commonly robot - works alongside humans
- range sensors (safe mode when humans too close)
- force sensors (halt operation when collision/impact detected)
- more compact & lightweight frame with soft round edges
5 robot configuration types & their major axes (schematic diagram & workspace)
Cartesian - PPP (accurate, heavy loads > pick-and-place, painting, rehabilitation after stroked)
Cylindrical - RPP
Spherical - RRP
SCARA (selective compliant articulated robot for assembly) - RRP
Articulated - RRR
Factors that determine workspace of manipulator
link lengths, joint types & limits, presence of limiters
4 common end effectors & applications
- Mechanical gripper for objects with uneven surfaces e.g. mugs
- suction for vacuum seal with flat even surface e.g. papers, glass sheets (control pressure better)
- screw e.g. insert nail into wall
- magnet e.g. magnetic objects
Specifications of a robot
- DOFs (planar manipulator has 2 translations & 1 rotation)
- no. of axes determine flexibility (major - arm positions wrist, minor - wrist orients end-effector)
- Workspace
- payload weight (max weight while remaining within other specifications)
- horizontal reach
- precision (resolution, accuracy, repeatability)
What is a robot?
Autonomy - makes independent decisions
Has sensors, actuators, control systems
Robot concerns
- Bias - based on learning e.g. fail to recognise certain ethnic groups
- Deception - to vulnerable users through emotional attachment/dependency
- Employment - displace certain classes of workers (retrain for better paid & less dangerous job)
- opacity - unjust decisions aren’t open to correction/transparent > GDPR - right to explanation
- safety - accidents
- Oversight - difficult to monitor & assess RAS (robots & autonomous systems) behaviour in open environments
- Privacy - allow stalker to track someone/law enforcement to track criminal
Robot principles
- Reflective equilibrium (assess benefits & drawbacks of institutions & judgement of trade off)
- Situational awareness (can drivers of AVs drive after a period of autonomous driving?)
- Participatory design for responsible innovation (reduce bias, understand impact on employment/privacy/safety/ practicality of oversight)
Purpose of robots
- dangerous environments (chemical spill cleanup, space exploration)
- boring & repetitive tasks (vehicle painting, part pick & place)
- high precision/speed (micro-surgery, precision machining)
- replace/augment human function (artificial limbs, exoskeleton)
Mechanical structure
- Arm - mobility, positions end-effector
- rigid bodies - links connected by joints
- wrist - at end of arm for angular position control
- end-effector - at moving end of manipulator to perform required task
Types of joints
Revolute (rotary)
Prismatic (translational)
Spherical (rotation at all 3 axis)
Screw (rotation & translation at 1 axis)
Redundant vs under-actuated manipulator
Redundant - extra DOF e.g. spatial manipulator with more than 6 DOFs to perform high dexterity tasks (avoid obstacles)
Under-actuated - fewer actuators than DOFs e.g. robot hand has 1 motor on a finger connected to a thread to have more DOFs
How to limit working range?
Add limiter/program limits so it doesn’t interfere with other links > understand configuration by drawing workspaces (operating envelopes)
Open-loop/serial kinematic chain
1/more link connected to only 1 other link
- higher payload (300 kg) (add more joints)
- larger workspace (less movement constraints)
- slower movements
- lower accuracy
Closed-loop/parallel kinematic chains
Every link in chain connected to at least 2 other links (forming 1/more closed loops)
- lower payload (2 kg)
- fewer DOF
- smaller workspace
- faster movements
- higher accuracy
Kinematic modelling
study of motion (trajectories, velocities, accelerations) without considering forces & moments responsible for motion
analytical relationship between joint positions & end effector pose
Forward kinematics
determine end-effector pose from joint variables (joint space to cartesian space)
Use homogeneous transformation matrix
Inverse kinematics
determine joint variables from desired end-effector pose (cartesian space to joint space)
Equations are generally nonlinear (multiple/infinite solutions, no closed form solution, no solution)
Differential kinematics
Relationship between joint velocity & end-effector velocity
Jacobian matrix finds the joint velocities required to achieve desired end-effector velocity (need to end-effector to move at constant velocity e.g. spraying paint on car)
x_dot = J*theta_dot
Homogeneous transformation matrix
single matrix of rotations and/or translations of a rigid body
Dynamic modelling
study of motion based on forces & torques
Solution approaches for inverse kinematics
- geometric (cosine rule)
- algebraic
— analytical/closed form (solve set of equations from homogeneous transformation matrix)
— iterative (numerical iteration toward desired goal position e.g. MatLab) when kinematic structure complex/unusual (no closed form solution)
Approaches for dynamic modelling
1) Lagrange-Euler (kinetic & potential energies) > L=K-P
2) Newton -Euler (conservation of linear & angular momentum for all links - apply F=ma to each link)
Kinetic energy of rotational system
1/2*theta_dot^2
*moment of inertia
Parallel axis theorem
I = I_cm + md^2
moment of inertia with respect to new axis
d is distance between 2 axis
Angular velocity
v = theta_dot*r
Joint (configuration) space scheme
1) Define task space waypoints
2) Solve inverse kinematics for each waypoint for each joint
3) Generate trajectory in* joint* space
4) Move joints according to this trajectory
5) Sensors monitor actual joint positions & velocities, correcting any discrepancies
Operational (cartesian) space scheme
1) Define task space waypoints
2) Generate trajectory from waypoints in task space
3) Solve inverse kinematics at each time step considering any errors provided by sensors
Joint space trajectory generation
- initial & final pose of end-effector
- initial & final velocities
- use inverse kinematics to calculate joint variables (find coefficients of cubic polynomial)
- for each joint, calculate smooth function to connect way points in joint space
- use nth order polynomial for (n+1) constraints
