Online motion synthesis with minimal intervention control and formal safety guarantees

Zeestraten, Martijn J.A.; Pereira, Aaron; Althoff, Matthias; Calinon, Sylvain

doi:10.1109/smc.2016.7844552

Cited by 8 publications

(5 citation statements)

References 21 publications

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“…This is an interesting research problem, whose solution would enhance this framework significantly. A potential approach for modulating the trajectory around obstacles is presented in [16].…”

Section: Discussionmentioning

confidence: 99%

Flexible Automation Driven by Demonstration: Leveraging Strategies that Simplify Robotics

Giusti

Zeestraten

İçer

et al. 2018

IEEE Robot. Automat. Mag.

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Section: Discussionmentioning

confidence: 99%

Flexible Automation Driven by Demonstration: Leveraging Strategies that Simplify Robotics

Giusti

Zeestraten

İçer

et al. 2018

IEEE Robot. Automat. Mag.

Self Cite

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“…Consider the point p i,1 , without loss of generality. In the below theorem and proof we adapt Proposition 1 in [19] to bound the maximum deviation from the line segment between p i,1 (s k+1 ) and p i,1 (s e ), when the maximum value of ∥ d 2 pi,1 ds 2 ∥ is known. This value can be found from the given trajectory and is denoted by α i .…”

Section: A Robot Occupancymentioning

confidence: 99%

Online verification of multiple safety criteria for a robot trajectory

Beckert

Pereira

Althoff

2017

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

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Abstract-Ensuring the safety of humans in a collaborative environment with industrial robots is a major concern of human-robot co-working. Most current approaches give no formal guarantee of safety; where such guarantees are given, accounting for the unpredictability of the human may limit robot efficiency. We therefore developed a novel trajectory planner for a robot arm, which formally guarantees the safety of humans from collision with the robot for every possible human behaviour, without restricting the robot more than necessary. To achieve this, the trajectory planner verifies online that the robot adheres to two separate safety criteria derived from ISO standards using reachable occupancies of surrounding humans and the robot. While one criterion anticipates all possible movements of the human and provides a reasonable safety guarantee, the other criterion additionally guarantees strict safety as long as the human behaves as expected according to ISO standards. We implemented the trajectory planner for a real robot arm and show some experimental results.

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“…excluding areas which are physically unreachable as much as possible. These requirements are essential in the context of a formally verifiable trajectory planner such as [7], [15]. The concept of a formally verified trajectory planner is that no movement is executed without being previously verified safe, see Fig.…”

Section: Problem Statement and Preliminariesmentioning

confidence: 99%

Calculating human reachable occupancy for guaranteed collision-free planning

Pereira

Althoff

2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-We address the problem of overapproximative short-term prediction of arm movement, for safe human-robot co-existence. A trajectory planner for a robot manipulator which formally verifies non-collision requires fast prediction of human future occupancy, which must be accurate yet still account for all possible human movement. This work presents two approaches to this: a novel, simple approach calculated directly in task space, and another approach using a kinematic model of the human based on the authors' previous work. We compare both approaches in an experimental setup with a robot manipulator. To the best of our knowledge, this is the first implementation and comparison of approaches to formally verified trajectory planning in human-robot co-working. We find that the novel approach has advantages in terms of ease and speed of computation and tightness at short time horizons and is more intuitive to extend to the whole human body; the previous approach offers advantages at longer prediction horizons. We also perform conformance checking to show that both approaches do indeed account for all relevant movement.

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Online motion synthesis with minimal intervention control and formal safety guarantees

Cited by 8 publications

References 21 publications

Flexible Automation Driven by Demonstration: Leveraging Strategies that Simplify Robotics

Flexible Automation Driven by Demonstration: Leveraging Strategies that Simplify Robotics

Online verification of multiple safety criteria for a robot trajectory

Calculating human reachable occupancy for guaranteed collision-free planning

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