Safety control of robots under Computed Torque control using reachable sets

Pereira, Aaron; Althoff, Matthias

doi:10.1109/icra.2015.7139020

Cited by 32 publications

(28 citation statements)

References 22 publications

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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%

“…Previous approaches, however, do not guarantee safety formally. The authors present in [7] an algorithm to formally verify robot motion (based on the paradigm of [8]), where the criterion of safety is that the human not be able to touch the robot while it is moving. In contrast to other methods, this approach uses a conservative prediction of the entire set in space that the human may occupy at future times, a Reachable Occupancy (RO), to ensure that the robot avoids the human before coming to a stop.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Problem Statement and Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

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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“…We focus on the former, though our approach may be adapted to the latter. Piecewise planning which formally guarantees noncollision is proposed by Petti and Fraichard for mobile robots [14] and adapted to serial-link robots in [2]. Our goal is to control a robot to complete a previously demonstrated task while formally guaranteeing that the trajectory used to complete the task is safe at all times.…”

Section: Introductionmentioning

confidence: 99%

“…Operating robots in such environments, however, requires safety guarantees. In previous work we showed how a robot trajectory can be formally verified online to guarantee safety of humans separated from the robot by a light curtain [2]; the robot will execute a previously verified controlled stop if the proposed trajectory is unsafe. Although the safe stops provide a formal safety guarantee, they might be avoided if the robot is allowed to deviate from its original trajectory.…”

Section: Introductionmentioning

confidence: 99%

Online motion synthesis with minimal intervention control and formal safety guarantees

Zeestraten

Pereira

Althoff

et al. 2016

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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Abstract-We present a framework for online coordinated obstacle avoidance with formal safety guarantees. Such a formally verified trajectory planner can be used in shared human-robot workspaces to guarantee safety. The obstacle avoidance is based on estimation of the human occupancy on two different time scales. A long-term plan is created based on a probabilistic task representation, learned by demonstration, and an estimate of the human occupancy to be avoided. Using an additional overapproximative, short-term prediction of human motion we guarantee that the robot can always account for sudden or reflex movements. We demonstrate our two-level obstacle avoidance in simulation. The results show that our method reduces the number of safety stops one would encounter when using only the formal safety verification, and synthesizes alternative movement plans that preserves the coordination observed in the original demonstrations.

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“…A method such as [2] uses a simple, online prediction of the future human occupancy to ensure that the robot is able to stop before the human can reach it, and thus ensure safety. However, this guarantee of safety relies on the prediction being overapproximative, i.e.…”

Section: Introductionmentioning

confidence: 99%

Reachset Conformance Testing of Human Arms with a Biomechanical Model

Stark¹,

Pereira²,

Althoff³

2018

2018 Second IEEE International Conference on Robotic Computing (IRC)

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Abstract-Guaranteeing safety in human-robot co-existence often requires a prediction of the volume that could be occupied by the human up to a future time, in order to avoid collisions. Such predictions should be simple and fast for real-time calculation and collision-checking, but account even for unexpected movement. We use a complex biomechanical model to search for extreme human movement, to validate such a prediction. Since the model has a large input space and highly nonlinear dynamics, we use an exploration algorithm based on RRTs to efficiently find the extreme movements. We find that the simple prediction encloses all arm positions found by the exploration algorithm, except where the biomechanical model does not account for collision between body tissue.

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Safety control of robots under Computed Torque control using reachable sets

Cited by 32 publications

References 22 publications

Calculating human reachable occupancy for guaranteed collision-free planning

Calculating human reachable occupancy for guaranteed collision-free planning

Online motion synthesis with minimal intervention control and formal safety guarantees

Reachset Conformance Testing of Human Arms with a Biomechanical Model

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