High-Performance Robot Control and Planning

High-Performance Robot Control and Planning

This project explores advanced control and planning algorithms, and their applicability to robotics problems. To achieve reliable robot operations that satisfy given performance specifications, we apply nonlinear, robust, predictive and hybrid controls approaches and adaptive motion planning.

 

Related Publications

[DOI] A modular framework for motion planning using safe-by-design motion primitives
M. Vukosavljev, Z. Kroeze, A. P. Schoellig, and M. E. Broucke
IEEE Transactions on Robotics, vol. 35, iss. 5, p. 1233–1252, 2019.
[View BibTeX] [View Abstract] [Download PDF] [View Video] [More Information]

In this paper, we present a modular framework for solving a motion planning problem among a group of robots. The proposed framework utilizes a finite set of low-level motion primitives to generate motions in a gridded workspace. The constraints on allowable sequences of motion primitives are formalized through a maneuver automaton . At the high level, a control policy determines which motion primitive is executed in each box of the gridded workspace. We state general conditions on motion primitives to obtain provably correct behavior so that a library of safe-by-design motion primitives can be designed. The overall framework yields a highly robust design by utilizing feedback strategies at both the low and high levels. We provide specific designs for motion primitives and control policies suitable for multirobot motion planning; the modularity of our approach enables one to independently customize the designs of each of these components. Our approach is experimentally validated on a group of quadrocopters.

@article{vukosavljev-tro19,
title = {A modular framework for motion planning using safe-by-design motion primitives},
author = {Marijan Vukosavljev and Zachary Kroeze and Angela P. Schoellig and Mireille E. Broucke},
journal = {{IEEE Transactions on Robotics}},
year = {2019},
volume = {35},
number = {5},
pages = {1233--1252},
doi = {10.1109/TRO.2019.2923335},
urlvideo = {http://tiny.cc/modular-3alg},
urllink = {https://arxiv.org/abs/1905.00495},
abstract = {In this paper, we present a modular framework for solving a motion planning problem among a group of robots. The proposed framework utilizes a finite set of low-level motion primitives to generate motions in a gridded workspace. The constraints on allowable sequences of motion primitives are formalized through a maneuver automaton . At the high level, a control policy determines which motion primitive is executed in each box of the gridded workspace. We state general conditions on motion primitives to obtain provably correct behavior so that a library of safe-by-design motion primitives can be designed. The overall framework yields a highly robust design by utilizing feedback strategies at both the low and high levels. We provide specific designs for motion primitives and control policies suitable for multirobot motion planning; the modularity of our approach enables one to independently customize the designs of each of these components. Our approach is experimentally validated on a group of quadrocopters.}
}

Adaptive model predictive control for high-accuracy trajectory tracking in changing conditions
K. Pereida and A. P. Schoellig
in Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, p. 7831–7837.
[View BibTeX] [View Abstract] [Download PDF] [More Information]

Robots and automated systems are increasingly being introduced to unknown and dynamic environments where they are required to handle disturbances, unmodeled dynamics, and parametric uncertainties. Robust and adaptive control strategies are required to achieve high performance in these dynamic environments. In this paper, we propose a novel adaptive model predictive controller that combines model predictive control (MPC) with an underlying L_1 adaptive controller to improve trajectory tracking of a system subject to unknown and changing disturbances. The L_1 adaptive controller forces the system to behave in a predefined way, as specified by a reference model. A higher-level model predictive controller then uses this reference model to calculate the optimal reference input based on a cost function, while taking into account input and state constraints. We focus on the experimental validation of the proposed approach and demonstrate its effectiveness in experiments on a quadrotor. We show that the proposed approach has a lower trajectory tracking error compared to non-predictive, adaptive approaches and a predictive, non-adaptive approach, even when external wind disturbances are applied.

@INPROCEEDINGS{pereida-iros18,
author={Karime Pereida and Angela P. Schoellig},
title={Adaptive Model Predictive Control for High-Accuracy Trajectory Tracking in Changing Conditions},
booktitle={{Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}},
year={2018},
pages={7831--7837},
urllink={https://arxiv.org/abs/1807.05290},
abstract={Robots and automated systems are increasingly being introduced to unknown and dynamic environments where they are required to handle disturbances, unmodeled dynamics, and parametric uncertainties. Robust and adaptive control strategies are required to achieve high performance in these dynamic environments. In this paper, we propose a novel adaptive model predictive controller that combines model predictive control (MPC) with an underlying L_1 adaptive controller to improve trajectory tracking of a system subject to unknown and changing disturbances. The L_1 adaptive controller forces the system to behave in a predefined way, as specified by a reference model. A higher-level model predictive controller then uses this reference model to calculate the optimal reference input based on a cost function, while taking into account input and state constraints. We focus on the experimental validation of the proposed approach and demonstrate its effectiveness in experiments on a quadrotor. We show that the proposed approach has a lower trajectory tracking error compared to non-predictive, adaptive approaches and a predictive, non-adaptive approach, even when external wind disturbances are applied.},
}

[DOI] Hybrid model predictive control for crosswind stabilization of hybrid airships
J. F. M. Foerster, M. K. Helwa, X. Du, and A. P. Schoellig
in Proc. of the International Symposium on Experimental Robotics (ISER), 2018, pp. 499-510.
[View BibTeX] [View Abstract] [Download PDF] [More Information]

Hybrid airships are heavier-than-air vehicles that generate a majority of the lift using buoyancy. The resulting high energy efficiency during operation and short take-off and landing distances make this vehicle class very suited for a number of logistics applications. However, the range of safe operating conditions can be limited due to a high susceptibility to crosswinds during taxiing, take-off and landing. The goal of this work is to design and implement an automated counter-gust system (CGS) that stabilizes a hybrid airship against wind disturbances during ground operations by controlling thrusters that are mounted to the wingtips. The CGS controller should compute optimal control inputs, run autonomously without pilot intervention, be computationally efficient to run on onboard hardware, and be flexible regarding adaption to future aircraft.

@INPROCEEDINGS{foerster-iser18,
author={Julian F. M. Foerster and Mohamed K. Helwa and Xintong Du and Angela P. Schoellig},
title={Hybrid Model Predictive Control for Crosswind Stabilization of Hybrid Airships},
booktitle={{Proc. of the International Symposium on Experimental Robotics (ISER)}},
year={2018},
pages={499-510},
doi={10.1007/978-3-030-33950-0_43},
urllink={https://link.springer.com/chapter/10.1007/978-3-030-33950-0_43},
abstract={Hybrid airships are heavier-than-air vehicles that generate a majority of the lift using buoyancy. The resulting high energy efficiency during operation and short take-off and landing distances make this vehicle class very suited for a number of logistics applications. However, the range of safe operating conditions can be limited due to a high susceptibility to crosswinds during taxiing, take-off and landing. The goal of this work is to design and implement an automated counter-gust system (CGS) that stabilizes a hybrid airship against wind disturbances during ground operations by controlling thrusters that are mounted to the wingtips. The CGS controller should compute optimal control inputs, run autonomously without pilot intervention, be computationally efficient to run on onboard hardware, and be flexible regarding adaption to future aircraft.},
}

[DOI] A framework for multi-vehicle navigation using feedback-based motion primitives
M. Vukosavljev, Z. Kroeze, M. E. Broucke, and A. P. Schoellig
in Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017, p. 223–229.
[View BibTeX] [View Abstract] [Download PDF] [View Video] [Download Slides] [More Information]

We present a hybrid control framework for solving a motion planning problem among a collection of heterogenous agents. The proposed approach utilizes a finite set of low-level motion primitives, each based on a piecewise affine feedback control, to generate complex motions in a gridded workspace. The constraints on allowable sequences of successive motion primitives are formalized through a maneuver automaton. At the higher level, a control policy generated by a shortest path non-deterministic algorithm determines which motion primitive is executed in each box of the gridded workspace. The overall framework yields a highly robust control design on both the low and high levels. We experimentally demonstrate the efficacy and robustness of this framework for multiple quadrocopters maneuvering in a 2D or 3D workspace.

@INPROCEEDINGS{vukosavljev-iros17,
author={Marijan Vukosavljev and Zachary Kroeze and Mireille E. Broucke and Angela P. Schoellig},
title={A Framework for Multi-Vehicle Navigation Using Feedback-Based Motion Primitives},
booktitle={{Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}},
year={2017},
pages={223--229},
doi={10.1109/IROS.2017.8202161},
urllink={https://arxiv.org/abs/1707.06988},
urlvideo={https://www.youtube.com/watch?v=qhDQyvYNVEc},
urlslides = {../../wp-content/papercite-data/slides/vukosavljev-iros17-slides.pdf},
abstract={We present a hybrid control framework for solving a motion planning problem among a collection of heterogenous agents. The proposed approach utilizes a finite set of low-level motion primitives, each based on a piecewise affine feedback control, to generate complex motions in a gridded workspace. The constraints on allowable sequences of successive motion primitives are formalized through a maneuver automaton. At the higher level, a control policy generated by a shortest path non-deterministic algorithm determines which motion primitive is executed in each box of the gridded workspace. The overall framework yields a highly robust control design on both the low and high levels. We experimentally demonstrate the efficacy and robustness of this framework for multiple quadrocopters maneuvering in a 2D or 3D workspace.},
}

[DOI] On the construction of safe controllable regions for affine systems with applications to robotics
M. K. Helwa and A. P. Schoellig
in Proc. of the IEEE Conference on Decision and Control (CDC), 2016, pp. 3000-3005.
[View BibTeX] [View Abstract] [Download PDF] [View Video] [Download Slides] [More Information]

This paper studies the problem of constructing in-block controllable (IBC) regions for affine systems. That is, we are concerned with constructing regions in the state space of affine systems such that all the states in the interior of the region are mutually accessible through the region’s interior by applying uniformly bounded inputs. We first show that existing results for checking in-block controllability on given polytopic regions cannot be easily extended to address the question of constructing IBC regions. We then explore the geometry of the problem to provide a computationally efficient algorithm for constructing IBC regions. We also prove the soundness of the algorithm. Finally, we use the proposed algorithm to construct safe speed profiles for fully-actuated robots and for ground robots modeled as unicycles with acceleration limits.

@INPROCEEDINGS{helwa-cdc16,
author = {Mohamed K. Helwa and Angela P. Schoellig},
title = {On the construction of safe controllable regions for affine systems with applications to robotics},
booktitle = {{Proc. of the IEEE Conference on Decision and Control (CDC)}},
year = {2016},
pages = {3000-3005},
doi = {10.1109/CDC.2016.7798717},
urllink = {https://arxiv.org/abs/1610.01243},
urlslides = {../../wp-content/papercite-data/slides/helwa-cdc16-slides.pdf},
urlvideo = {https://youtu.be/s_N7zTtCjd0},
abstract = {This paper studies the problem of constructing in-block controllable (IBC) regions for affine systems. That is, we are concerned with constructing regions in the state space of affine systems such that all the states in the interior of the region are mutually accessible through the region’s interior by applying uniformly bounded inputs. We first show that existing results for checking in-block controllability on given polytopic regions cannot be easily extended to address the question of constructing IBC regions. We then explore the geometry of the problem to provide a computationally efficient algorithm for constructing IBC regions. We also prove the soundness of the algorithm. Finally, we use the proposed algorithm to construct safe speed profiles for fully-actuated robots and for ground robots modeled as unicycles with acceleration limits.},
}

[DOI] Safe and robust quadrotor maneuvers based on reach control
M. Vukosavljev, I. Jansen, M. E. Broucke, and A. P. Schoellig
in Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2016, pp. 5677-5682.
[View BibTeX] [View Abstract] [Download PDF] [View Video] [Download Slides] [Download 2nd Slides] [More Information]

In this paper, we investigate the synthesis of piecewise affine feedback controllers to execute safe and robust quadrocopter maneuvers. The methodology is based on formulating the problem as a reach control problem on a polytopic state space. Reach control has so far only been developed in theory and has not been tested experimentally in a real system before. We demonstrate that these theoretical tools can achieve aggressive, albeit safe and robust, quadrocopter maneuvers without the need for a predefined open-loop reference trajectory. In a proof-of-concept demonstration, the reach controller is implemented in one translational direction while the other degrees of freedom are stabilized by separate controllers. Experimental results on a quadrocopter show the effectiveness and robustness of this control approach.

@INPROCEEDINGS{vukosavljev-icra16,
author = {Marijan Vukosavljev and Ivo Jansen and Mireille E. Broucke and Angela P. Schoellig},
title = {Safe and robust quadrotor maneuvers based on reach control},
booktitle = {{Proc. of the IEEE International Conference on Robotics and Automation (ICRA)}},
year = {2016},
pages = {5677-5682},
doi = {10.1109/ICRA.2016.7487789},
urllink = {https://arxiv.org/abs/1610.02385},
urlvideo={https://youtu.be/l4vdxdmd2xc},
urlslides={../../wp-content/papercite-data/slides/vukosavljev-icra16-slides.pdf},
urlslides2={../../wp-content/papercite-data/slides/vukosavljev-icra16-slides2.pdf},
abstract = {In this paper, we investigate the synthesis of piecewise affine feedback controllers to execute safe and robust quadrocopter maneuvers. The methodology is based on formulating the problem as a reach control problem on a polytopic state space. Reach control has so far only been developed in theory and has not been tested experimentally in a real system before. We demonstrate that these theoretical tools can achieve aggressive, albeit safe and robust, quadrocopter maneuvers without the need for a predefined open-loop reference trajectory. In a proof-of-concept demonstration, the reach controller is implemented in one translational direction while the other degrees of freedom are stabilized by separate controllers. Experimental results on a quadrocopter show the effectiveness and robustness of this control approach.}
}

[DOI] Speed daemon: experience-based mobile robot speed scheduling
C. J. Ostafew, A. P. Schoellig, T. D. Barfoot, and J. Collier
in Proc. of the International Conference on Computer and Robot Vision (CRV), 2014, pp. 56-62. Best Robotics Paper Award.
[View BibTeX] [View Abstract] [Download PDF] [View Video]

A time-optimal speed schedule results in a mobile robot driving along a planned path at or near the limits of the robot’s capability. However, deriving models to predict the effect of increased speed can be very difficult. In this paper, we present a speed scheduler that uses previous experience, instead of complex models, to generate time-optimal speed schedules. The algorithm is designed for a vision-based, path-repeating mobile robot and uses experience to ensure reliable localization, low path-tracking errors, and realizable control inputs while maximizing the speed along the path. To our knowledge, this is the first speed scheduler to incorporate experience from previous path traversals in order to address system constraints. The proposed speed scheduler was tested in over 4 km of path traversals in outdoor terrain using a large Ackermann-steered robot travelling between 0.5 m/s and 2.0 m/s. The approach to speed scheduling is shown to generate fast speed schedules while remaining within the limits of the robot’s capability.

@INPROCEEDINGS{ostafew-crv14,
author = {Chris J. Ostafew and Angela P. Schoellig and Timothy D. Barfoot and J. Collier},
title = {Speed daemon: experience-based mobile robot speed scheduling},
booktitle = {{Proc. of the International Conference on Computer and Robot Vision (CRV)}},
pages = {56-62},
year = {2014},
doi = {10.1109/CRV.2014.16},
urlvideo = {https://youtu.be/Pu3_F6k6Fa4?list=PLC12E387419CEAFF2},
abstract = {A time-optimal speed schedule results in a mobile robot driving along a planned path at or near the limits of the robot's capability. However, deriving models to predict the effect of increased speed can be very difficult. In this paper, we present a speed scheduler that uses previous experience, instead of complex models, to generate time-optimal speed schedules. The algorithm is designed for a vision-based, path-repeating mobile robot and uses experience to ensure reliable localization, low path-tracking errors, and realizable control inputs while maximizing the speed along the path. To our knowledge, this is the first speed scheduler to incorporate experience from previous path traversals in order to address system constraints. The proposed speed scheduler was tested in over 4 km of path traversals in outdoor terrain using a large Ackermann-steered robot travelling between 0.5 m/s and 2.0 m/s. The approach to speed scheduling is shown to generate fast speed schedules while remaining within the limits of the robot's capability.},
note = {Best Robotics Paper Award}
}

[DOI] Dance of the flying machines: methods for designing and executing an aerial dance choreography
F. Augugliaro, A. P. Schoellig, and R. D’Andrea
IEEE Robotics Automation Magazine, vol. 20, iss. 4, pp. 96-104, 2013.
[View BibTeX] [View Abstract] [Download PDF] [View Video] [Download Slides]

Imagine a troupe of dancers flying together across a big open stage, their movement choreographed to the rhythm of the music. Their performance is both coordinated and skilled; the dancers are well rehearsed, and the choreography well suited to their abilities. They are no ordinary dancers, however, and this is not an ordinary stage. The performers are quadrocopters, and the stage is the ETH Zurich Flying Machine Arena, a state-of-the-art mobile testbed for aerial motion control research.

@ARTICLE{augugliaro-ram13,
author = {Federico Augugliaro and Angela P. Schoellig and Raffaello D'Andrea},
title = {Dance of the Flying Machines: Methods for Designing and Executing an Aerial Dance Choreography},
journal = {{IEEE Robotics Automation Magazine}},
volume = {20},
number = {4},
pages = {96-104},
year = {2013},
doi = {10.1109/MRA.2013.2275693},
urlvideo={http://youtu.be/NRL_1ozDQCA?t=21s},
urlslides={../../wp-content/papercite-data/slides/augugliaro-ram13-slides.pdf},
abstract = {Imagine a troupe of dancers flying together across a big open stage, their movement choreographed to the rhythm of the music. Their performance is both coordinated and skilled; the dancers are well rehearsed, and the choreography well suited to their abilities. They are no ordinary dancers, however, and this is not an ordinary stage. The performers are quadrocopters, and the stage is the ETH Zurich Flying Machine Arena, a state-of-the-art mobile testbed for aerial motion control research.}
}

[DOI] Generation of collision-free trajectories for a quadrocopter fleet: a sequential convex programming approach
F. Augugliaro, A. P. Schoellig, and R. D’Andrea
in Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012, pp. 1917-1922.
[View BibTeX] [View Abstract] [Download PDF] [View Video]

This paper presents an algorithm that generates collision-free trajectories in three dimensions for multiple vehicles within seconds. The problem is cast as a non-convex optimization problem, which is iteratively solved using sequential convex programming that approximates non-convex constraints by using convex ones. The method generates trajectories that account for simple dynamics constraints and is thus independent of the vehicle’s type. An extensive a posteriori vehicle-specific feasibility check is included in the algorithm. The algorithm is applied to a quadrocopter fleet. Experimental results are shown.

@INPROCEEDINGS{augugliaro-iros12,
author = {Federico Augugliaro and Angela P. Schoellig and Raffaello D'Andrea},
title = {Generation of collision-free trajectories for a quadrocopter fleet: A sequential convex programming approach},
booktitle = {{Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}},
pages = {1917-1922},
year = {2012},
doi = {10.1109/IROS.2012.6385823},
urlvideo = {https://youtu.be/wwK7WvvUvlI?list=PLD6AAACCBFFE64AC5},
abstract = {This paper presents an algorithm that generates collision-free trajectories in three dimensions for multiple vehicles within seconds. The problem is cast as a non-convex optimization problem, which is iteratively solved using sequential convex programming that approximates non-convex constraints by using convex ones. The method generates trajectories that account for simple dynamics constraints and is thus independent of the vehicle's type. An extensive a posteriori vehicle-specific feasibility check is included in the algorithm. The algorithm is applied to a quadrocopter fleet. Experimental results are shown.}
}

[DOI] Feed-forward parameter identification for precise periodic quadrocopter motions
A. P. Schoellig, C. Wiltsche, and R. D’Andrea
in Proc. of the American Control Conference (ACC), 2012, pp. 4313-4318.
[View BibTeX] [View Abstract] [Download PDF] [View Video] [Download Slides]

This paper presents an approach for precisely tracking periodic trajectories with a quadrocopter. In order to improve temporal and spatial tracking performance, we propose a feed-forward strategy that adapts the motion parameters sent to the vehicle controller. The motion parameters are either adjusted on the fly or, in order to avoid initial transients, identified prior to the flight performance. We outline an identification scheme that tunes parameters for a large class of periodic motions, and requires only a small number of identification experiments prior to flight. This reduced identification is based on analysis and experiments showing that the quadrocopter’s closed-loop dynamics can be approximated by three directionally decoupled linear systems. We show the effectiveness of this approach by performing a sequence of periodic motions on real quadrocopters using the tuned parameters obtained by the reduced identification.

@INPROCEEDINGS{schoellig-acc12,
author = {Angela P. Schoellig and Clemens Wiltsche and Raffaello D'Andrea},
title = {Feed-forward parameter identification for precise periodic quadrocopter motions},
booktitle = {{Proc. of the American Control Conference (ACC)}},
pages = {4313-4318},
year = {2012},
doi = {10.1109/ACC.2012.6315248},
urlvideo = {http://tiny.cc/MusicInMotion},
urlslides = {../../wp-content/papercite-data/slides/schoellig-acc12-slides.pdf},
abstract = {This paper presents an approach for precisely tracking periodic trajectories with a quadrocopter. In order to improve temporal and spatial tracking performance, we propose a feed-forward strategy that adapts the motion parameters sent to the vehicle controller. The motion parameters are either adjusted on the fly or, in order to avoid initial transients, identified prior to the flight performance. We outline an identification scheme that tunes parameters for a large class of periodic motions, and requires only a small number of identification experiments prior to flight. This reduced identification is based on analysis and experiments showing that the quadrocopter's closed-loop dynamics can be approximated by three directionally decoupled linear systems. We show the effectiveness of this approach by performing a sequence of periodic motions on real quadrocopters using the tuned parameters obtained by the reduced identification.}
}

University of Toronto Institute for Aerospace Studies