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Intuitive operation and programming of

highly redundant mobile manipulators

Dipl.-Inf.

Christian Scheurer

Corporate Research

KUKA Deutschland GmbH

Augsburg, Germany


Robotic Revolutions


Current challenges in programming robots

o Programming with teach pendants

o Time-consuming

o Experience essential

o Redundant robots


o Collaborative robots with force-based interaction

o Teaching by handguidance

o Sensitive in applications

o Safe for human-robot collaboration

o Collaborative mobile robots with whole-body control

o Redundancy

o Teaching by handguidance

o Reactive control

o Ongoing work: Collaborative mobile dual arm robots

Agenda


Why collaboration with force-based robot interaction?


Motivation

Robots are currently evolving from stupid machines performing repetitive tasks behind safety fences to intelligent robotic co – workers.

Force is the most intuitive input


State of the art in collaborative robotics


LBR iiwa – Handguiding and collision detection in real industrial applications

Handguiding the KUKA LBR iiwa Collision detection enabling human-robot collaboration


Our research projects depend on safe, intuitive, force-based interaction


Conceptual Formulation


Conceptual Formulation

Goal: Have a robotic co-worker with full interactivity

“Friendly” behavior also in the proximity to constraints

Respect always all constraints

Research Questions:

How to satisfy all constraints?

What if the human makes a task infeasible?

How to handle disturbances due to human interaction?

Robot communicates what it thinks about the human intervention

What to communicate back?


Methods


Reactive, whole-body control taking sensor data into account

Task 1: Avoid joint position limits

Task 2: Avoid vel and acc limits

Task 3: Follow trajectory (example)

Task 4: Keep elbow up (example)

Task 5: …

Task N: Minimize kinetic energy

Task

Pri

ori

ty

Impedance control (already in industry) Reactive control with task priorization on kinematics level (CLIK, SNS*) Reactive control with task priorization on dynamics level (OSC**)

* F. Flacco, A. De Luca and O. Khatib, "Motion control of redundant robots under joint constraints: Saturation in the Null Space," 2012 IEEE International Conference on Robotics and Automation, 2012, pp. 285-292.

** O. Khatib, "A unified approach for motion and force control of robot manipulators: The operational space formulation," in IEEE Journal on Robotics and Automation, vol. 3, no. 1, pp. 43-53, February 1987.


Local minimization of joint velocities

The Jacobian represents the kinematic model of the robot

It does not contain information about bounds in joint space

𝒒 = 𝑱1# 𝒙1 + (𝑱2𝑷1)

#(𝒙2 − 𝑱2𝑱1# 𝒙1 )

𝒒 = 𝑱# 𝒙

Task priorization on kinematic level (1st order)

TASK 1

TASK 2

NSP

𝒒𝟏 = 𝑱𝟏# 𝒙𝟏

𝑷1 = 𝑰𝑛 − 𝑱1# 𝑱1

𝒒𝟐 = (𝑱2𝑷1)#(𝒙𝟐 − 𝑱2𝑱𝟏

# 𝒙𝟏 )

Bounds on joint velocities/accelerations?

Task activation / deactivation?

Discontinuities?


Saturation in the null space - algorithm

SNS in principle:

1. If joint limit (position/velocity/acceleration)

reached

2. If task no longer feasible

Saturate the joint at its maximum/minimum position/velocity/acceleration and try to achieve the task with the remaining joints

Scale the task velocity

TASK SCALING

JOINT SATURATION


Task 1: Avoid joint position limits

Task 2: Avoid vel and acc limits



Task 5: …

Task N: Minimize kinetic energy

Task

Pri

ori

ty

Constraint 1: Joint Position Limits

Constraint 2: Joint Velocity limits

Constraint 3: Joint Acceleration Limits

Taks N: Minimize Kinetic Energy



Task

Pri

ori

ty

Con

stra

ints

Constraints handled with saturation in the null space (SNS)


SNS on vel - Flow chart Check Feasibility

Compute Solution

YES

NO

Output Solution

Output Best Solution found

Saturate most critical joint

Any redundancy

left?

YES

NO

Store Scaled Solution

Joint Motion

Feasible?


SNS on vel - Flow chart

Initialization

𝑔𝑒𝑛𝑒𝑟𝑖𝑐 𝑝𝑠𝑒𝑢𝑑𝑜𝑖𝑛𝑣𝑒𝑟𝑠𝑒

Check Feasibility

Output Solution

𝒒 𝑪𝑮



Any redundancy

left?

YES

NO


𝒒 = 𝑱# 𝒙

YES

NO

Joint Motion

Feasible?



Initialization


𝑠, 𝑗 = 𝑔𝑒𝑡𝑆𝑐𝑎𝑙𝑖𝑛𝑔𝐹𝑎𝑐𝑡𝑜𝑟(𝒂, 𝒃)

YES

NO

Output Solution

𝒒 𝑪𝑮



Any redundancy

left?

YES

NO


𝑠 ≥ 1 ?



Initialization



YES

NO

𝒒 𝑶𝒖𝒕 = 𝒒 𝑪𝑮

𝒒 𝑪𝑮



Any redundancy

left?

YES

NO


𝑠 ≥ 1 ?



Initialization



YES

NO


𝒒 𝑪𝑮



Any redundancy

left?

YES

NO

YES

NO

𝑠 > 𝑠∗ ? 𝑠∗ = 𝑠

𝑠 ≥ 1 ?



Initialization



YES

NO


𝒒 𝑪𝑮

Output Best Solution found Any

redundancy left?

YES

NO

YES

NO

𝑠 > 𝑠∗ ? 𝑠∗ = 𝑠

𝑠 ≥ 1 ?



Initialization



YES

NO


𝒒 𝑪𝑮


YES

YES

NO

𝑠 > 𝑠∗ ? 𝑠∗ = 𝑠

?

𝑠 ≥ 1 ?

NO

≥



Initialization



YES

NO


𝒒 𝑪𝑮

YES

YES

NO

𝑠 > 𝑠∗ ? 𝑠∗ = 𝑠

?

𝑠 ≥ 1 ?

≥

NO


𝑄𝑚𝑖𝑛 ≤ 𝑞 ≤ 𝑄𝑚𝑎𝑥

𝑉𝑚𝑖𝑛 ≤ 𝑞 ≤ 𝑉𝑚𝑎𝑥

𝐴𝑚𝑖𝑛 ≤ 𝑞 ≤ 𝐴𝑚𝑎𝑥

Saturation in the nullspace (SNS)

Shaping the joint velocity bounds

Joint range

Velocity range

Acceleration range

Admissible Area

Constraint 1: Joint Limits

Constraint 2: Joint Velocity Limits

Constraint 3: Joint Acceleration LImits

⇔

𝑞 = 𝑞ℎ

𝑞ℎ+1 ≅ 𝑞ℎ + 𝑞 ℎ𝑇 𝑉𝑚𝑖𝑛 ≤ 𝑞 ℎ ≤ 𝑉𝑚𝑎𝑥

𝑄𝑚𝑖𝑛 − 𝑞ℎ𝑇

≤ 𝑞 ℎ ≤𝑄𝑚𝑎𝑥 − 𝑞ℎ

𝑇

− 2𝐴𝑚𝑎𝑥 𝑞ℎ − 𝑄𝑚𝑖𝑛 ≤ 𝑞 ℎ ≤

2𝐴𝑚𝑎𝑥(𝑄𝑚𝑖𝑛 − 𝑞ℎ)


Solution with saturated joints and task scaling


Time-free motion – Motion interruption by a human operator

Implementation of SNS on force / torque level Define the task what to do here: from MURAB project, ultrasonic scanning of a breast Time less important in human robot interaction tasks


Communicate relevant information to a robot programmer: e.g. joint limit

I have an uncomfortable configuration.

Please move joint 3 up!

Offline programming tools, e.g. KUKA.Sim On Sunrise Controller / tech pendant


Communicate relevant information to a robot programmer: e.g. joint limit

I have an uncomfortable configuration.

Please move joint 3 up!


Collaborative mobile robots with whole-body control


Aim → Mobile manipulators in aerospace automation safely cooperating with human workers

Conditions

Dynamic environment

Changing environment

Semi-structured to fully unstructured environment

Requirements

Be safe

Deal with uncertainties

Get the job done

Hardware solution → VALERI robot concept

Software solution → New reactive control strategies taking sensor information into account

VALERI (EU, 2013-2015) – Robot requirements for aerospace industry

http://www.valeri-project.eu/


VALERI (EU, 2013-2015) – Mapping of task space to joint space


e.g. Following a Cartesian Trajectory with the VALERI

m = 6

n = 12 m-n = 6 redundant DOFs (∞6 𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛𝑠 𝑡𝑜 𝑡ℎ𝑒 𝐼𝐾 𝑝𝑟𝑜𝑏𝑙𝑒𝑚)

𝒙 = 𝑱𝒒

Joint Space Mapping Task Space

m-dimensional Space n-dimensional Space

𝒙, 𝒙 𝒒, 𝒒 𝑱 ∈ ℝ𝑚.𝑛

𝑱#

𝒒 = 𝑱# 𝒙


VALERI (EU, 2013-2015) – General project results

True mobile manipulation, Coordinated 12DOF movement, redundancy resolution

Extended workspace with mobile platform and linear axes

New safety concepts, workspace surveillance, tactile skin

Use cases in aerospace industry: sealing and visual inspection (continuous path applications)



VALERI (EU, 2013-2015) – Whole-body control for executing tasks



VALERI (EU, 2013-2015) – Handguiding and reactive control using the redundancy


Reactive control and redundancy resolution based on laser scanner information and self-collision model

Handguiding the unified kinematics of the mobile manipulator VALERI based on force input and a redundancy resolution sceme


VALERI (EU, 2013-2015) – Kinematic independent teaching of Cartesian tasks


Idea: Teach a Cartesian trajectory by handguiding only „the tool“ Robot joint trajectories solved by task priorization framework Here: Handguiding a different mobile manipulator (teach-in), execute on a different kinematics


Ongoing work: Collaborative mobile dual arm robots


Hybr-iT (BMBF, 2016-2019) – Project overview

Mobile dual arm manipulation

Human-Robot Collaboration

Modular software and hardware End user: Volkswagen, Airbus

Goal: Build and evaluate a mobile dual arm robot in production-near assembly applications


Hybr-iT (BMBF, 2016-2019) - Interaction with a dual arm robot

Here: stationary dual arm robot Load sharing with two robot arms Interaction using coupling stiffness with Cartesian impedance for both arms


Hybr-iT (BMBF, 2016-2019) – Redundancy resolution for a mobile dual arm robot

Two Cartesian tasks given: position hold for one arm, linear motion for other arm Solving redundancy for complete robot Platform motion to support task execution of both arms


Conclusion

Collaborative robots evolving from stationary single arm to mobile dual arm robots Need and approaches for force-based human robot interaction Handling of redundancy for the unified mobile manipulator system in a task priorization framework Need and approaches for easy and fast programming of complex mobile robot systems Handguidance Cartesian task specification and automatic redundancy resolution instead of joint or motion programming


Thank you for your attention!

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