RoManOV

Team RoManOV
f20180590@goa.bits-pilani.ac.in

Introduction
Environment Setup
Theoretical Background
Design Requirements
Design Implementation
Testing and Review

Abbreviations

DOF Degrees Of Freedom
ROS Robot Operating System
EE End-Effector
WC Wrist Center
DH Denavit–Hartenberg
FK Forward Kinematics
IK Inverse Kinematics
RRR Revolute Revolute Revolute
URDF Unified Robot Description Format

1. Introduction

This project originated from one of the final projects we had kept for a summer term course conducted by the project founding members. You may refer to this repository for further details on the course conducted.

^{Fig. 1.1 The current model of RoManOV developed and simulated in Gazebo}

Objective

The goal here is to build a robotic arm that can autonomously recognise, pick and place objects and ultimately perform complex tasks like playing a game of chess using Convolutional Neural Networks, Deep Learning and Computer Vision.

2. Environment Setup

The project uses ROS Kinetic Kame running on Ubuntu 16.04 LTS (Xenial Xerus).

The following tools are planning to be used for simulation and motion planning:

Gazebo: a physics based 3D simulator extensively used in the robotics world
RViz: a 3D visualizer for sensor data analysis, and robot state visualization
MoveIt!: a ROS based software framework for motion planning, kinematics and robot control
MATLAB & Simulink: a multi-paradigm numerical computing environment and proprietary programming language

We'll update the README.md file on the Environment setup, once the setup is done. For MATLAB & Simulink simulations, you may refer to this.

3. Theoretical Background

The following theoretical concepts will be used in this project:

Generalized Coordinates and Degrees of Freedom
Rotation matrices and composition of rotations
Euler angles and Euler theorem
Homogeneous transforms
Denavit–Hartenberg parameters
Forward and Inverse Kinematics
Computer Vision
Deep Learning
Object Learning
Applications using Neural Networks
Contrast Limited Adaptive Histogram Equalisation (CLAHE)
Stockfish

3.1 Serial Manipulators

Serial manipulators are robots composed of an assembly of links connected by joints (a Kinematic Chain), and the most common types of robots in industry.

Generalized Coordinates

Generalized coordinates are parameters that are used to uniquely describe the instantaneous dynamical configuration of a rigid multi-body system relative to some reference configuration. In the robotics of serial manipulators, they are used to define the configuration space or joint space, which refers to the set of all possible configurations a manipulator may have.

Degrees of Freedom

The degree of freedom (DOF) of a rigid body or mechanical system is the number of independent parameters or coordinates that fully define its configuration in free space.

Common DOFs:

6: coordinates required to fully describe the configuration of a rigid body in 3D free space
12: coordinates required to fully describe simultaneously the configuration of two separate rigid bodies in 3D free space
7: coordinates required to fully describe the configuration of two rigid bodies in 3D free space connected by a joint

^{Fig. 3.1 Geometry of a 3-DOF anthropomorphic robot}
^{[Source: Narong Aphiratsakun. AIT]}

The serial manipulator shown in figure 3.1 has n=3 joints: each a revolute with 1-DOF. Each joint connects with two links, making the total number of links, n+1 = 4, including the fixed base link.

Therefore, the total number of DOF for any serial manipulator with three 1-DOF joints is:

Note: The DOF of a serial manipulator with only revolute and/or prismatic joints is always equal to the number of its joints, except when both ends of the manipulator are fixed (closed chain linkage).

Workspace

The workspace of a robotic manipulator is defined as the set of points that can be reached by its end-effector ^[2]. In other words, it is simply the 3D space in which the robot mechanism works.

^{Fig. 3.2 Workspaces of 3-DOF SCARA and anthropomorphic manipulators}
^{[Source: Federica.EU]}

Figure 3.2 shows two types of serial manipulators, SCARA and Anthropomorphic with their associated workspaces. Figure 3.1 also shows the workspace of the 3-DOF manipulator from a top and side perspective.

It is important to note that no kinematic solution exists for the manipulator's configuration or joint space for any desired end-effector position outside of the workspace.

Spherical Wrist

A spherical wrist of a robotic manipulator is designed by arranging its last three revolute joints such that their axes of rotations intersect at a common point, referred to as the wrist center.

^{Fig. 3.3 Difference between a spherical and non-spherical wrist}
^{[Source: Khaled Elashry, ResearchGate]}

Figure 3.3 shows the difference between a spherical and non-spherical wrist. In 3.3 (a), joint axes of rotations A, B, C all intersect at the wrist center, whereas, in 3.3(b), the wrist center is non-existent. Physically speaking, a six DOF serial manipulator like the one in figure 3.3 would use the first three joints to control the position of the wrist center while the last three joints (spherical wrist) would orient the end effector as needed, as in a human arm.

The spherical wrist is an important design characteristic in anthropomorphic manipulators which simplifies their kinematic analysis, as demonstrated in section 5.

3.2 Rotation of Coordinate Frames

Rotation matrices are a means of expressing a vector in one coordinate frame in terms of some other coordinate frame.

^{Fig. 3.4 A 2D geometric rotation between coordinate frames A and B}

In figure 3.2, Point P is expressed with vector u relative to coordinate frame B. The objective is to express point P with vector v relative to coordinate frame A. The basis vectors of v, v_x and v_y can be expressed in terms of the basis vectors of u, u_x and u_y as follows:

where unit vectors of frame A, a_x and a_y are expressed in terms of unit vectors of frame B, b_x and b_y as follows:

Substituting (2) in (1) and solving for the dot products yields the following equation:

where the first term on the right-hand side is the 2D Rotation Matrix, denoted in this case as ^a_bR. Any point on coordinate frame B multiplied by ^a_bR will project it onto frame A. In other words, to express a vector u on some frame B as a vector v on a different frame A, u is multiplied by the rotation matrix with angle theta by which frame A is rotated from fram B. Also worth noting is that the rotation from A to B is equal to the transpose of the rotation of B to A.

3.3 Euler Angles

Euler angles are a system to describe a sequence or a composition of rotations. According to Euler's Rotation Theorem, the orientation of any rigid body w.r.t. some fixed reference frame can always be described by three elementary rotations in a given sequence as shown in figure 3.3.

^{Fig. 3.5 Defining Euler angles from a sequence of rotations}
^{[Source: CHRobotics]}

Conventionally, the movements about the three axes of rotations and their associated angles are described by the 3D rotation matrices in figure 3.4.

^{Fig. 3.6 3D counter-clockwise rotation matrices describing yaw, pitch and roll}

Euler angles are characterized by the following properties:

Tait-Bryan vs. Classic
Rotation Order
Intrinsic (body fixed) vs. Extrinsic (fixed axes) rotations

Intrinsic or body-fixed rotations are performed about the coordinate system as rotated by the previous rotation. The rotation sequence changes the axis orientation after each elemental rotation while the body remains fixed.

In an intrinsic sequence of rotations, such as, a Z-Y-X convention of a yaw, followed by a pitch, followed by a roll, subsequent elemental rotations are post-multiplied.

Extrinsic or fixed-axis rotations are performed about the fixed world reference frame. The original coordinate frame remains motionless while the body changes orientation.

In an extrinsic sequence of rotations, such as, a Z-Y-X convention of a yaw, followed by a pitch, followed by a roll, subsequent elemental rotations are pre-multiplied.

Note: An extrinsic rotation sequence of A, B, C = an intrinsic rotation sequence of C, B, A.

Euler angles, normally in the Tait–Bryan, Z-X-Y convention, are also used in robotics for describing the degrees of freedom of a spherical wrist of a robotic manipulator.

Of particular importance is a phenomenon associated with Euler angles known as a Gimbal Lock which occurs when there is a loss of one degree of freedom as a result of the axes of two of the three gimbals driven into a parrallel configuration.

3.4 Homogeneous Transforms

In the case where a reference frame is both simultaneously rotated and translated (transformed) with respect to some other reference frame, a homogeneous transform matrix describes the transformation.

^{Fig. 3.7 Rotation and Translation of frame B relative to frame A}
^{[Source: Salman Hashmi. BSD License]}

In figure 3.7, point P is expressed w.r.t. frame B and the objective is to express it w.r.t. frame A. To do so would require projecting or superimposing frame B onto frame A i.e. first rotating frame B to orient it with frame A and then translating it such that the centers B₀ and A₀ of both frames are aligned.

The relationship between the three vectors in figure 3.7 is shown in equation (1). The desired vector to point P from A₀ is the sum of the vector to point P from B₀, rotated to frame A, and the translation vector to B₀ w.r.t A₀. Equations (2) and (3) are the matrix-forms of equation (1) so that it can be rendered in software with linear algebra libraries.

^{Fig. 3.8 Anatomy of the homogeneous transform relationship}

Figure 3.8 describes the components of equation (2). The desired vector to point P (w.r.t. to A₀) is obtained by multiplying the given vector to point P (w.r.t. B₀) by the homogeneous transform matrix, composed of the block Rotation matrix projecting B onto A and the block translation vector to B w.r.t A₀.

^{Fig. 3.9 Transformation between adjacent revolute joint frames}

As shown in figure 3.9, the position of the end-effector is known w.r.t. its coordinate reference frame C. The objective is to express it w.r.t. the fixed world coordinate reference frame W. This is because the positions of all objects of interest in the manipulator's environment are expressed w.r.t. the world reference frame. In other worlds, both, the end-effector, and the objects it interacts with need to be defined on the same coordinate reference frame.

Point P relative to frame W can be found by successively applying equation (4) between adjacent joints:

The above process can be summarized in terms of equation (1) with ^W_CT being the desired composite homogeneous transform that projects frame C onto frame W.

3.5 Denavit–Hartenberg parameters

Before the homogeneous transforms between adjacent links can be computed, the coordinate frames of the joint links on which the transforms are applied must be defined. The Denavit–Hartenberg (DH) parameters are four parameters describing the rotations and translations between adjacent links. The definition of these parameters constitutes a convention for assigning coordinate reference frames to the links of a robotic manipulator. Figure 3.8 shows the so-called modified convention of DH parameters as defined by [Craig, JJ. (2005)].

^{Fig. 3.8 The four parameters of the Modified DH convention}
^{[Source: Modified from Wikipedia Commons]}

The parameters are defined as follows:

α_i-1: twist angle between the z-axes of links i-1 and i (measured about x_i-1 in a right-hand sense)
ɑ_i-1: link distance between the z-axes of links i-1 and i (measured x_i-1)
d_i: link offset signed distance between the x-axes of links i-1 and i (measured along z_i)
θ_i: joint angle between the x-axes of links i-1 and i (measured about z_i in a right-hand sense)

Note:

The origin of a frame i is defined by the intersection of x_i and z_i
The x-axes define the common normals between z_i-1 and z_i

Recall that to compute the position of the end-effector w.r.t. the base or world reference frame, transforms between adjacent links are composed as follows:

where the base frame is denoted by 0 and the end-effector's frame denoted by N. Thus, ⁰_NT defines the homogeneous transformation that projects frame N onto frame 0. More specifically, a single transform between links i-1 and i is given by

and is made up up of two rotations R of magnitudes α and θ, and two displacements D of magnitudes ɑ and d.

The parameter assignment process for open kinematic chains with n degrees of freedom (i.e., joints) is summarized as:

Label all joints from {1, 2, … , n}.
Label all links from {0, 1, …, n} starting with the fixed base link as 0.
Draw lines through all joints, defining the joint axes.
Assign the Z-axis of each frame to point along its joint axis.
Identify the common normal between each frame Z_i-1 and Z_i
The endpoints of intermediate links (i.e., not the base link or the end effector) are associated with two joint axes, {i} and {i+1}. For i from 1 to n-1, assign the X_i to be ...
1. For skew axes, along the normal between Z_i and Z_i+1 and pointing from {i} to {i+1}.
2. For intersecting axes, normal to the plane containing Z_i and Z_i+1.
3. For parallel or coincident axes, the assignment is arbitrary; look for ways to make other DH parameters equal to zero.
For the base link, always choose frame {0} to be coincident with frame {1} when the first joint variable (θ₁ or d₁) is equal to zero. This will guarantee that α₀ = a₀ = 0, and, if joint 1 is a revolute, d₁ = 0. If joint 1 is prismatic, then θ₁ = 0.
For the end effector frame, if joint n is revolute, choose X_n to be in the direction of X_n−1 when θ_n = 0 and the origin of frame {n} such that d_n = 0.

Special cases involving the Z_i-1 and Z_i axes:

collinear lines: alpha = 0 and a = 0
parallel lines: alpha = 0 and a ≠ 0
intersecting lines: alpha ≠ 0 and a = 0
If the common normal intersects Z_i at the origin of frame i, then d_i is zero.

Once the frame assignments are made, the DH parameters are typically presented in tabular form (below). Each row in the table corresponds to the homogeneous transform from frame {i} to frame {i+1}.

^{Table 3.1 The four parameters of the Modified DH convention}

3.6 Forward and Inverse Kinematics

Forward Kinematics is the process of computing a manipulator's end-effector position in Cartesian coordinates from its given joint angles. This can be achieved by a composition of homogeneous transformations that map the base frame onto the end-effector's frame, taking as input the joint angles. The end-effector's coordinates can then be extracted from the resulting composite transform matrix.

The relationship between Forward and Inverse Kinematics is depicted in figure 3.9,

^{Fig. 3.9 Relationship between Forward and Inverse Kinematics}

Inverse Kinematics is the reverse process where the EE position is known and a set of joint angles that would result in that position need to be determined. This is a more complicated process than FK as multiple solutions can exist for the same EE position. However, no joint angle solutions exist for any EE position outside the manipulator's workspace. There are two main approaches to solve the IK problem: numerical and analytical. The later approach is used in this project.

4. Design Requirements

The scope of the design is limited to a single pick-and-place cycle that consists of the following steps:

Movement of EE towards the target object
Grasping/picking the target object
Movement towards the drop-site
Dropping/placing the object at the drop-site

Figure 4.1 shows these steps in Gazebo.

^{Fig 4.1 A single pick-and-place cycle}
^{[Source: Gazebo]}

The primary metrics of interest are:

Percentage of success in a total of 10 pick-and-place cycles
Error in the calculated EE position trajectory (via FK) compared to the EE position received in the IK service request
Time taken to execute a complete pick-and-place cycle

^{Fig 4.2 Planned EE trajectory to drop-off location}
^{[Source: RViz, MoveIt!]}

Table 4.1 shows the criteria on which the project is evaluated,

^{Table 4.1 Project evaluation criteria}

The minimum criteria is to achieve a success rate of at least 80% with an EE trajectory error not greater than 0.5.

abhidxt299/RoManOV_Simulation