My friends call me Alex. I work at Meta Reality Labs in San Francisco, researching how to move virtual avatars to imitate human movement, e.g. from a Quest headset. This work touches fields like reinforcement learning, motion-tracking and character animation. I got my PhD from ETH Zurich, where I worked on robot motion-planning and trajectory optimization for quadruped robots. This work gave me a solid understanding of the physics of legged locomotion, model-based control and how contacts are used to move floating-base systems. Now that I moved into computer graphics, I'm using my understanding of these physical constraints to synthesize highest quality animations.

Happy to get in touch,

Projects

Highlighting some projects here. For videos on all projects, see my Youtube.

QuestSim: Human Motion Tracking from sparse Sensors using Simulated Avatars
Character Animation Reinforcement Learning Motion Capture

pdfwebsite

Gait and Trajectory Optimization for legged systems through Phase-based Endeffector Parameterization

Robotics Motion and Path Planning Trajectory Optimization

pdfsummary video

Thesis: Optimization-based motion-planning for legged robots

Legged Locomotion Trajectory Optimization Nonlinear Programming

pdf

Why walking is difficult

3 min read

We're used to seeing cars drive around and drones flying over our heads. Why is it much more difficult to make machines walk?

Models for legged robots

30 min read

To approximate the physics of legged robots mathematically, there exists a variety of models (RBD, Centroidal, SRBD, LIPM). Here we explain their differences and underlying assumptions

Trajectory Optimization

10 min read

How to formulate a mathematical problem so it captures the physics of walking? A solution to this problem gives us motions-plans to execute on a robot.

Publication List

Download pdfs, videos, slides, bibtex info and more. See also Google Scholar.

QuestSim: Human Motion Tracking from Sparse Sensors with Simulated Avatars. Winkler, A.; Won, J; Ye, Y. SIGGRAPH Asia. 2022
pdf   video   bibtex
            @inproceedings{10.1145/3550469.3555411,
              author = {Winkler, Alexander and Won, Jungdam and Ye, Yuting},
              title = {QuestSim: Human Motion Tracking from Sparse Sensors with Simulated Avatars},
              year = {2022},
              isbn = {9781450394703},
              publisher = {Association for Computing Machinery},
              address = {New York, NY, USA},
              url = {https://doi.org/10.1145/3550469.3555411},
              doi = {10.1145/3550469.3555411},
              booktitle = {SIGGRAPH Asia 2022 Conference Papers},
              articleno = {2},
              numpages = {8},
              keywords = {Reinforcement Learning, Motion Tracking, Character Animation, Wearable Devices},
              location = {Daegu, Republic of Korea},
              series = {SA '22}
              }
          
Transformer Inertial Poser: Real-time Human Motion Reconstruction from Sparse IMUs with Simultaneous Terrain Generation. Yifeng Jiang, Yuting Ye, Deepak Gopinath, Jungdam Won, Alexander W Winkler, C Karen Liu. SIGGRAPH Asia. 2022
pdf   video   bibtex
                @inproceedings{10.1145/3550469.3555428,
                  author = {Jiang, Yifeng and Ye, Yuting and Gopinath, Deepak and Won, Jungdam and Winkler, Alexander W. and Liu, C. Karen},
                  title = {Transformer Inertial Poser: Real-Time Human Motion Reconstruction from Sparse IMUs with Simultaneous Terrain Generation},
                  year = {2022},
                  isbn = {9781450394703},
                  publisher = {Association for Computing Machinery},
                  address = {New York, NY, USA},
                  url = {https://doi.org/10.1145/3550469.3555428},
                  doi = {10.1145/3550469.3555428},
                  booktitle = {SIGGRAPH Asia 2022 Conference Papers},
                  articleno = {3},
                  numpages = {9},
                  keywords = {Wearable Devices, Human Motion, Inertial Measurement Units},
                  location = {Daegu, Republic of Korea},
                  series = {SA '22}
                  }
              
PhD Thesis: Optimization-based motion planning for legged robots. Winkler, A. W Ph.D. Thesis, ETH Zurich. 2018
Optimization-based motion planning for legged robots [pdf] pdf   Optimization-based motion planning for legged robots [link] slides   bibtex
@phdthesis{winkler18_phd,
            author    = {Winkler, Alexander W},
            title     = {Optimization-based motion planning for legged robots},
            publisher = {ETH Zurich},
            year      = {2018},
            school    = {ETH Zurich},
            doi       = {10.3929/ethz-b-000272432},
          }
          
Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization. Winkler, A. W; Bellicoso, D. C; Hutter, M.; and Buchli, J. IEEE Robotics and Automation Letters (RA-L). 2018
Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization [pdf] pdf   Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization [link] video   bibtex
            @article{winkler18,
              author    = {Winkler, Alexander W and 
                          Bellicoso, Dario C and 
                          Hutter, Marco and
                          Buchli, Jonas},
              title     = {Gait and Trajectory Optimization for Legged Systems 
                          through Phase-based End-Effector Parameterization},
              journal   = {IEEE Robotics and Automation Letters (RA-L)},
              year      = {2018},
              month     = {July},
              pages     = {1560-1567},
              doi       = {10.1109/LRA.2018.2798285},
              volume    = {3},
              keywords  = {legged locomotion, trajectory optimization}
            }
          
Fast Trajectory Optimization for Legged Robots using Vertex-based ZMP Constraints. Winkler, A. W; Farshidian, F.; Pardo, D.; Neunert, M.; and Buchli, J. IEEE Robotics and Automation Letters (RA-L). 2017
Fast Trajectory Optimization for Legged Robots using Vertex-based ZMP Constraints [pdf] pdf   Fast Trajectory Optimization for Legged Robots using Vertex-based ZMP Constraints [link] video   bibtex
                  @article{winkler17b,
                  author    = {Winkler, Alexander W and 
                              Farshidian, Farbod and 
                              Pardo, Diego and 
                              Neunert, Michael and 
                              Buchli, Jonas},
                  title     = {Fast Trajectory Optimization for Legged Robots 
                              using Vertex-based ZMP Constraints},
                  journal   = {IEEE Robotics and Automation Letters (RA-L)},
                  year      = {2017},
                  month     = {oct},
                  pages     = {2201-2208},
                  doi       = {10.1109/LRA.2017.2723931},
                  volume    = {2},
                  keywords  = {legged locomotion, trajectory optimization}
                }
                
Robust Whole-Body Motion Control of Legged Robots. Farshidian, F.; Jelavic, E.; Winkler, A. W; and Buchli, J. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2017
Robust Whole-Body Motion Control of Legged Robots [pdf] pdf   Robust Whole-Body Motion Control of Legged Robots [link] video   bibtex   abstract
@inproceedings{farshidian17b,
  author    = {Farshidian, Farbod and 
               Jelavic, Edo and
               Winkler, Alexander W and
               Buchli, Jonas},
  title     = {Robust Whole-Body Motion Control of Legged Robots},
  booktitle = {IEEE/RSJ International Conference on 
               Intelligent Robots and Systems (IROS)},
  year      = {2017},
  abstract  = {We introduce a robust control architecture for
               the whole-body motion control of torque controlled robots
               with arms and legs. The method is based on the robust
               control of contact forces in order to track a planned Center
               of Mass trajectory. Its appeal lies in the ability to guarantee
               robust stability and performance despite rigid body model
               mismatch, actuator dynamics, delays, contact surface stiffness,
               and unobserved ground profiles. Furthermore, we introduce a
               task space decomposition approach which removes the coupling
               effects between contact force controller and the other noncontact
               controllers. Finally, we verify our control performance
               on a quadruped robot and compare its performance to a
               standard inverse dynamics approach on hardware.}            
}

We introduce a robust control architecture for the whole-body motion control of torque controlled robots with arms and legs. The method is based on the robust control of contact forces in order to track a planned Center of Mass trajectory. Its appeal lies in the ability to guarantee robust stability and performance despite rigid body model mismatch, actuator dynamics, delays, contact surface stiffness, and unobserved ground profiles. Furthermore, we introduce a task space decomposition approach which removes the coupling effects between contact force controller and the other noncontact controllers. Finally, we verify our control performance on a quadruped robot and compare its performance to a standard inverse dynamics approach on hardware.
Hybrid direct collocation and control in the constraint- consistent subspace for dynamic legged robot locomotion. Pardo, D.; Neunert, M.; Winkler, A. W; Grandia, R.; and Buchli, J. In Robotics, Science and Systems (RSS). 2017
Hybrid direct collocation and control in the constraint- consistent subspace for dynamic legged robot locomotion [pdf] pdf   Hybrid direct collocation and control in the constraint- consistent subspace for dynamic legged robot locomotion [link] video   Hybrid direct collocation and control in the constraint- consistent subspace for dynamic legged robot locomotion [link] link   bibtex   abstract
@inproceedings{pardo17,
  author    = {Pardo, Diego and
               Neunert, Michael and 
               Winkler, Alexander W and
               Grandia, Ruben and
               Buchli, Jonas},
  title     = {Hybrid direct collocation and control in the constraint-
               consistent subspace for dynamic legged robot locomotion},
  booktitle = {Robotics, Science and Systems (RSS)},
  year      = {2017},
  abstract  = {In this paper, we present an algorithm for optimal planning and
               control of legged robot locomotion. Given the desired contact 
               sequence, this method generates gaits and dynamic motions for 
               legged robots without resorting to simplified stability criteria. 
               The method uses direct collocation for searching for solutions 
               within the constraint-consistent subspace defined by the robot’s 
               contact configuration. For the differential equation constraints 
               of the collocation algorithm, we use the so-called direct 
               dynamics of a constrained multibody system. The dynamics of a 
               legged robot is different for each contact configuration. Our 
               method deals with such a hybrid nature, and it allows for 
               velocity discontinuities when contacts are made. We introduce 
               the projected impact dynamics constraint to enforce consistency 
               during mode switching. We stabilize the plan using an inverse 
               dynamics controller consistent with the constraints and 
               compatible with the optimal feed-forward control of the motion 
               plan. As a whole, this approach reduces the complexity associated 
               with specifying dynamic motions of a floating-base robot under 
               the constant influence of contact forces. We apply this method 
               on a hydraulically actuated quadruped robot. We show two type of 
               gaits on the physical system (walking and trotting), and other 
               dynamic motions in simulation (jumping and leaping). The results 
               presented here are one of the few examples of an optimal control 
               problem satisfactorily solved and transferred to a real 
               torque-controlled legged robot.},       
}

In this paper, we present an algorithm for optimal planning and control of legged robot locomotion. Given the desired contact sequence, this method generates gaits and dynamic motions for legged robots without resorting to simplified stability criteria. The method uses direct collocation for searching for solutions within the constraint-consistent subspace defined by the robot’s contact configuration. For the differential equation constraints of the collocation algorithm, we use the so-called direct dynamics of a constrained multibody system. The dynamics of a legged robot is different for each contact configuration. Our method deals with such a hybrid nature, and it allows for velocity discontinuities when contacts are made. We introduce the projected impact dynamics constraint to enforce consistency during mode switching. We stabilize the plan using an inverse dynamics controller consistent with the constraints and compatible with the optimal feed-forward control of the motion plan. As a whole, this approach reduces the complexity associated with specifying dynamic motions of a floating-base robot under the constant influence of contact forces. We apply this method on a hydraulically actuated quadruped robot. We show two type of gaits on the physical system (walking and trotting), and other dynamic motions in simulation (jumping and leaping). The results presented here are one of the few examples of an optimal control problem satisfactorily solved and transferred to a real torque-controlled legged robot.
Online Walking Motion and Foothold Optimization for Quadruped Locomotion. Winkler, A. W; Farshidian, F.; Neunert, M.; Pardo, D.; and Buchli, J. In IEEE International Conference on Robotics and Automation (ICRA). 2017
Online Walking Motion and Foothold Optimization for Quadruped Locomotion [pdf] pdf   Online Walking Motion and Foothold Optimization for Quadruped Locomotion [link] video   Online Walking Motion and Foothold Optimization for Quadruped Locomotion [link] slides   Online Walking Motion and Foothold Optimization for Quadruped Locomotion [link] link   doi   bibtex   abstract
@inproceedings{winkler17a,
  author    = {Winkler, Alexander W and 
               Farshidian, Farbod and 
               Neunert, Michael and 
               Pardo, Diego and 
               Buchli, Jonas},
  title     = {Online Walking Motion and Foothold Optimization 
               for Quadruped Locomotion},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  year      = {2017},
  pages     = {5308-5313},
  doi       = {10.1109/ICRA.2017.7989624},
  abstract  = {We present an algorithm that generates walking
               motions for quadruped robots without the use of an explicit
               footstep planner by simultaneously optimizing over both the
               Center of Mass (CoM) trajectory and the footholds. Feasibility
               is achieved by imposing stability constraints on the CoM
               related to the Zero Moment Point and explicitly enforcing
               kinematic constraints between the footholds and the CoM
               position. Given a desired goal state, the problem is solved 
               online by a Nonlinear Programming solver to generate the walking
               motion. Experimental trials show that the algorithm is able to
               generate walking gaits for multiple steps in milliseconds that
               can be executed on a real quadruped robot.} 
}

We present an algorithm that generates walking motions for quadruped robots without the use of an explicit footstep planner by simultaneously optimizing over both the Center of Mass (CoM) trajectory and the footholds. Feasibility is achieved by imposing stability constraints on the CoM related to the Zero Moment Point and explicitly enforcing kinematic constraints between the footholds and the CoM position. Given a desired goal state, the problem is solved online by a Nonlinear Programming solver to generate the walking motion. Experimental trials show that the algorithm is able to generate walking gaits for multiple steps in milliseconds that can be executed on a real quadruped robot.
An Efficient Optimal Planning and Control Framework For Quadrupedal Locomotion. Farshidian, F.; Neunert, M.; Winkler, A. W; Rey, G.; and Buchli, J. In IEEE International Conference on Robotics and Automation (ICRA). 2017
An Efficient Optimal Planning and Control Framework For Quadrupedal Locomotion [pdf] pdf   An Efficient Optimal Planning and Control Framework For Quadrupedal Locomotion [link] video   An Efficient Optimal Planning and Control Framework For Quadrupedal Locomotion [link] link   doi   bibtex   abstract
@inproceedings{farshidian17a,
  author    = {Farshidian, Farbod and 
              Neunert, Michael and 
              Winkler, Alexander W and 
              Rey, Gonzalo and 
              Buchli, Jonas},
  title     = {An Efficient Optimal Planning and Control Framework 
              For Quadrupedal Locomotion},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  year      = {2017},
  pages     = {93-100},
  doi       = {10.1109/ICRA.2017.7989016},
  abstract  = {In this paper, we present an efficient Dynamic
               Programing framework for optimal planning and control of
               legged robots. First we formulate this problem as an optimal
               control problem for switched systems. Then we propose a
               multi–level optimization approach to find the optimal switching
               times and the optimal continuous control inputs. Through
               this scheme, the decomposed optimization can potentially be
               done more efficiently than the combined approach. Finally,
               we present a continuous-time constrained LQR algorithm
               which simultaneously optimizes the feedforward and feedback
               controller with O(n) time-complexity. In order to validate our
               approach, we show the performance of our framework on a
               quadrupedal robot. We choose the Center of Mass dynamics
               and the full kinematic formulation as the switched system model
               where the switching times as well as the contact forces and the
               joint velocities are optimized for different locomotion tasks 
               such as gap crossing, walking and trotting.}
}

In this paper, we present an efficient Dynamic Programing framework for optimal planning and control of legged robots. First we formulate this problem as an optimal control problem for switched systems. Then we propose a multi–level optimization approach to find the optimal switching times and the optimal continuous control inputs. Through this scheme, the decomposed optimization can potentially be done more efficiently than the combined approach. Finally, we present a continuous-time constrained LQR algorithm which simultaneously optimizes the feedforward and feedback controller with O(n) time-complexity. In order to validate our approach, we show the performance of our framework on a quadrupedal robot. We choose the Center of Mass dynamics and the full kinematic formulation as the switched system model where the switching times as well as the contact forces and the joint velocities are optimized for different locomotion tasks such as gap crossing, walking and trotting.
Trajectory Optimization Through Contacts and Automatic Gait Discovery for Quadrupeds. Neunert, M.; Farshidian, F.; Winkler, A. W.; and Buchli, J. IEEE Robotics and Automation Letters (RA-L). 2017
Trajectory Optimization Through Contacts and Automatic Gait Discovery for Quadrupeds [pdf] pdf   Trajectory Optimization Through Contacts and Automatic Gait Discovery for Quadrupeds [link] video   Trajectory Optimization Through Contacts and Automatic Gait Discovery for Quadrupeds [link] link   doi   bibtex   abstract
@article{neunert2017,
  author    = {Michael Neunert and 
               Farbod Farshidian and 
               Alexander W. Winkler and 
               Jonas Buchli},
  title     = {Trajectory Optimization Through Contacts and 
               Automatic Gait Discovery for Quadrupeds},
  journal   = {IEEE Robotics and Automation Letters (RA-L)},
  year      = {2017},
  pages     = {1502-1509},
  volume    = {2},
  doi       = {10.1109/LRA.2017.2665685},
  abstract  = {In this work we present a Trajectory Optimization
               framework for whole-body motion planning through contacts.
               We demonstrate how the proposed approach can be applied to
               automatically discover different gaits and dynamic motions on a
               quadruped robot. In contrast to most previous methods, we do
               not pre-specify contact-switches, -timings, -points or gait 
               patterns, but they are a direct outcome of the optimization. 
               Furthermore, we optimize over the entire dynamics of the robot, 
               which enables the optimizer to fully leverage the capabilities of
               the robot. To illustrate the spectrum of achievable motions, we 
               show eight different tasks, which would require very different 
               control structures when solved with state-of-the-art methods. 
               Using our Trajectory Optimization approach, we are solving each 
               task with a simple, high level cost function and without any 
               changes in the control structure. Furthermore, we fully integrate
               our approach with the robot’s control and estimation framework 
               such that we are able to run the optimization online. Through 
               several hardware experiments we show that the optimized 
               trajectories and control inputs can be directly applied to 
               physical systems.},
  keywords  = {Multilegged Robots, Motion and Path Planning,
               Optimization and Optimal Control}
}

In this work we present a Trajectory Optimization framework for whole-body motion planning through contacts. We demonstrate how the proposed approach can be applied to automatically discover different gaits and dynamic motions on a quadruped robot. In contrast to most previous methods, we do not pre-specify contact-switches, -timings, -points or gait patterns, but they are a direct outcome of the optimization. Furthermore, we optimize over the entire dynamics of the robot, which enables the optimizer to fully leverage the capabilities of the robot. To illustrate the spectrum of achievable motions, we show eight different tasks, which would require very different control structures when solved with state-of-the-art methods. Using our Trajectory Optimization approach, we are solving each task with a simple, high level cost function and without any changes in the control structure. Furthermore, we fully integrate our approach with the robot’s control and estimation framework such that we are able to run the optimization online. Through several hardware experiments we show that the optimized trajectories and control inputs can be directly applied to physical systems.
Optimal and Learning Control for Autonomous Robots. Buchli, J.; Farshidian, F.; Winkler, A. W.; Sandy, T.; and Gifthaler, M. In arXiv. 2017
Optimal and Learning Control for Autonomous Robots [pdf] pdf   bibtex   abstract
@inproceedings{buchli2017,
  author    = {Jonas Buchli and 
               Farbod Farshidian and 
               Alexander W. Winkler and 
               Timothy Sandy and
               Markus Gifthaler},
  title     = {Optimal and Learning Control for Autonomous Robots},
  booktitle = {arXiv},
  year      = {2017},
  abstract  = {Optimal and Learning Control for Autonomous Robots has been taught 
               in the Robotics, Systems and Controls Masters at ETH Zurich with the 
               aim to teach optimal control and reinforcement learning for closed loop 
               control problems from a unified point of view. The starting point is the 
               formulation of of an optimal control problem and deriving the different 
               types of solutions and algorithms from there. These lecture notes aim at 
               supporting this unified view with a unified notation wherever possible, 
               and a bit of a translation help to compare the terminology and notation 
               in the different fields. The course assumes basic knowledge of Control 
               Theory, Linear Algebra and Stochastic Calculus.}
}

Optimal and Learning Control for Autonomous Robots has been taught in the Robotics, Systems and Controls Masters at ETH Zurich with the aim to teach optimal control and reinforcement learning for closed loop control problems from a unified point of view. The starting point is the formulation of of an optimal control problem and deriving the different types of solutions and algorithms from there. These lecture notes aim at supporting this unified view with a unified notation wherever possible, and a bit of a translation help to compare the terminology and notation in the different fields. The course assumes basic knowledge of Control Theory, Linear Algebra and Stochastic Calculus.
Evaluating direct transcription and nonlinear optimization methods for robot motion planning. Pardo, D.; Moeller, L.; Neunert, M.; Winkler, A. W.; and Buchli, J. IEEE Robotics and Automation Letters (RA-L). 2016
Evaluating direct transcription and nonlinear optimization methods for robot motion planning [pdf] pdf   Evaluating direct transcription and nonlinear optimization methods for robot motion planning [link] video   Evaluating direct transcription and nonlinear optimization methods for robot motion planning [link] link   doi   bibtex   abstract
@article{pardo16,
  author    = {Pardo, Diego and 
              Moeller, Lukas and 
              Neunert, Michael and 
              Winkler, Alexander W. and
              Buchli, Jonas},
  title     = {Evaluating direct transcription and nonlinear optimization 
              methods for robot motion planning},
  journal   = {IEEE Robotics and Automation Letters (RA-L)},
  pages     = {946-953},
  doi       = {10.1109/LRA.2016.2527062},
  year      = {2016},
  abstract  = {This paper studies existing direct transcription
               methods for trajectory optimization applied to robot motion
               planning. There are diverse alternatives for the implementation
               of direct transcription. In this study we analyze the effects of
               such alternatives when solving a robotics problem. Different
               parameters such as integration scheme, number of discretization
               nodes, initialization strategies and complexity of the problem
               are evaluated. We measure the performance of the methods in
               terms of computational time, accuracy and quality of the solu-
               tion. Additionally, we compare two optimization methodologies
               frequently used to solve the transcribed problem, namely Sequen-
               tial Quadratic Programming (SQP) and Interior Point Method
               (IPM). As a benchmark, we solve different motion tasks on an
               underactuated and non-minimal-phase ball-balancing robot with
               a 10 dimensional state space and 3 dimensional input space.
               Additionally, we validate the results on a simulated 3D quadrotor.
               Finally, as a verification of using direct transcription methods
               for trajectory optimization on real robots, we present hardware
               experiments on a motion task including path constraints and
               actuation limits.},
  keywords  = {Optimization and Optimal Control, Underactuated Robots},
}

This paper studies existing direct transcription methods for trajectory optimization applied to robot motion planning. There are diverse alternatives for the implementation of direct transcription. In this study we analyze the effects of such alternatives when solving a robotics problem. Different parameters such as integration scheme, number of discretization nodes, initialization strategies and complexity of the problem are evaluated. We measure the performance of the methods in terms of computational time, accuracy and quality of the solu- tion. Additionally, we compare two optimization methodologies frequently used to solve the transcribed problem, namely Sequen- tial Quadratic Programming (SQP) and Interior Point Method (IPM). As a benchmark, we solve different motion tasks on an underactuated and non-minimal-phase ball-balancing robot with a 10 dimensional state space and 3 dimensional input space. Additionally, we validate the results on a simulated 3D quadrotor. Finally, as a verification of using direct transcription methods for trajectory optimization on real robots, we present hardware experiments on a motion task including path constraints and actuation limits.
Planning and Execution of Dynamic Whole-Body Locomotion for a Hydraulic Quadruped on Challenging Terrain. Winkler, A. W.; Mastalli, C.; Havoutis, I.; Focchi, M.; Caldwell, D.; and Semini, C. In IEEE International Conference on Robotics and Automation (ICRA). 2015
Planning and Execution of Dynamic Whole-Body Locomotion for a Hydraulic Quadruped on Challenging Terrain [pdf] pdf   Planning and Execution of Dynamic Whole-Body Locomotion for a Hydraulic Quadruped on Challenging Terrain [link] video   Planning and Execution of Dynamic Whole-Body Locomotion for a Hydraulic Quadruped on Challenging Terrain [link] link   doi   bibtex   abstract
@inproceedings{winkler15,
  author    = {Winkler, Alexander W. and 
               Mastalli, Carlos and
               Havoutis, Ioannis and 
               Focchi, Michele and 
               Caldwell, Darwin and
               Semini, Claudio},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},   
  title     = {Planning and Execution of Dynamic Whole-Body Locomotion 
               for a Hydraulic Quadruped on Challenging Terrain},
  year      = {2015},
  pages     = {5148-5154},
  doi       = {10.1109/ICRA.2015.7139916},
  abstract  = {We present a framework for dynamic
               quadrupedal locomotion over challenging terrain, where
               the choice of appropriate footholds is crucial for the success
               of the behaviour. We build a model of the environment on-line
               and on-board using an efficient occupancy grid representation.
               We use Any-time-Repairing A* (ARA*) to search over a tree
               of possible actions, choose a rough body path and select the
               locally-best footholds accordingly. We run a n-step lookahead
               optimization of the body trajectory using a dynamic stability
               metric, the Zero Moment Point (ZMP), that generates natural
               dynamic whole-body motions. A combination of floating-base
               inverse dynamics and virtual model control accurately
               executes the desired motions on an actively compliant system.
               Experimental trials show that this framework allows us to
               traverse terrains at nearly 6 times the speed of our previous
               work, evaluated over the same set of trials.}
}

We present a framework for dynamic quadrupedal locomotion over challenging terrain, where the choice of appropriate footholds is crucial for the success of the behaviour. We build a model of the environment on-line and on-board using an efficient occupancy grid representation. We use Any-time-Repairing A* (ARA*) to search over a tree of possible actions, choose a rough body path and select the locally-best footholds accordingly. We run a n-step lookahead optimization of the body trajectory using a dynamic stability metric, the Zero Moment Point (ZMP), that generates natural dynamic whole-body motions. A combination of floating-base inverse dynamics and virtual model control accurately executes the desired motions on an actively compliant system. Experimental trials show that this framework allows us to traverse terrains at nearly 6 times the speed of our previous work, evaluated over the same set of trials.
On-line and on-board planning for quadrupedal locomotion, using practical, on-board perception. Mastalli, C.; Havoutis, I.; Winkler, A. W.; Caldwell, D.; and Semini, C. In IEEE International Conference on Practial Robot Applications. 2015
On-line and on-board planning for quadrupedal locomotion, using practical, on-board perception [pdf] pdf   bibtex   abstract
@inproceedings{mastalli2015,
  author    = {Mastalli, Carlos and 
               Havoutis, Ioannis and 
               Winkler, Alexander W. and  
               Caldwell, Darwin and 
               Semini, Claudio},
  booktitle = {IEEE International Conference on Practial Robot Applications},
  title     = {On-line and on-board planning for quadrupedal locomotion, 
               using practical, on-board perception},
  year      = {2015},
  abstract  = {We present a legged motion planning approach
               for quadrupedal locomotion over challenging terrain. We de-
               compose the problem into body action planning and footstep
               planning. We use a lattice representation together with a set of
               defined body movement primitives for computing a body action
               plan. The lattice representation allows us to plan versatile 
               move ments that ensure feasibility for every possible plan. To
               this end, we propose a set of rules that define the footstep 
               search regions and footstep sequence given a body action. We use
               Anytime Repairing A* (ARA*) search that guarantees bounded sub-
               optimal plans. Our main contribution is a planning approach
               that generates on-line versatile movements. Experimental trials
               demonstrate the performance of our planning approach in a
               set of challenging terrain conditions. The terrain information
               and plans are computed on-line and on-board.},
}

We present a legged motion planning approach for quadrupedal locomotion over challenging terrain. We de- compose the problem into body action planning and footstep planning. We use a lattice representation together with a set of defined body movement primitives for computing a body action plan. The lattice representation allows us to plan versatile move ments that ensure feasibility for every possible plan. To this end, we propose a set of rules that define the footstep search regions and footstep sequence given a body action. We use Anytime Repairing A* (ARA*) search that guarantees bounded sub- optimal plans. Our main contribution is a planning approach that generates on-line versatile movements. Experimental trials demonstrate the performance of our planning approach in a set of challenging terrain conditions. The terrain information and plans are computed on-line and on-board.
Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots. Winkler, A. W.; Havoutis, I.; Bazeille, S.; Ortiz, J.; Focchi, M.; Dillmann, R.; Caldwell, D.; and Semini, C. In IEEE International Conference on Robotics and Automation (ICRA). 2014
Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots [pdf] pdf   Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots [link] video   Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots [link] link   doi   bibtex   abstract
@inproceedings{winkler14,
  author    = {Winkler, Alexander W. and 
              Havoutis, Ioannis and 
              Bazeille, Stephane and 
              Ortiz, Jesus and 
              Focchi, Michele and 
              Dillmann, Ruediger and 
              Caldwell, Darwin and 
              Semini, Claudio},
  title     = {Path planning with force-based foothold adaptation and virtual 
               model control for torque controlled quadruped robots},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  pages     = {6476--6482},
  year      = {2014},
  doi       = {10.1109/ICRA.2014.6907815},
  isbn      = {9781479936847},
  abstract  = {We present a framework for quadrupedal locomotion over highly 
               challenging terrain where the choice of appropriate footholds 
               is crucial for the success of the behaviour. We use a path 
               planning approach which shares many similarities with the results
               of the DARPA Learning Locomotion challenge and extend it to 
               allow more flexibility and increased robustness. During 
               execution we incorporate an on-line force-based foothold 
               adaptation mechanism that updates the planned motion according 
               to the perceived state of the environment. This way we exploit 
               the active compliance of our system to smoothly interact with 
               the environment, even when this is inaccurately perceived or 
               dynamically changing, and update the planned path on-the-fly. 
               In tandem we use a virtual model controller that provides the
               feed-forward torques that allow increased accuracy together 
               with highly compliant behaviour on an otherwise naturally very
               stiff robotic system. We leverage the full set of benefits 
               that a high performance torque controlled quadruped robot can 
               provide and demonstrate the flexibility and robustness of our 
               approach on a set of experimental trials of increasing 
               difficulty.}
}

We present a framework for quadrupedal locomotion over highly challenging terrain where the choice of appropriate footholds is crucial for the success of the behaviour. We use a path planning approach which shares many similarities with the results of the DARPA Learning Locomotion challenge and extend it to allow more flexibility and increased robustness. During execution we incorporate an on-line force-based foothold adaptation mechanism that updates the planned motion according to the perceived state of the environment. This way we exploit the active compliance of our system to smoothly interact with the environment, even when this is inaccurately perceived or dynamically changing, and update the planned path on-the-fly. In tandem we use a virtual model controller that provides the feed-forward torques that allow increased accuracy together with highly compliant behaviour on an otherwise naturally very stiff robotic system. We leverage the full set of benefits that a high performance torque controlled quadruped robot can provide and demonstrate the flexibility and robustness of our approach on a set of experimental trials of increasing difficulty.
Path Planning and Adaptive Execution based on Force-Feedback for Quadruped Locomotion. Winkler, A. W. Technical Report Karlsruhe Institute of Technology and Italian Institute of Technology. Masters Thesis, 2013
Path Planning and Adaptive Execution based on Force-Feedback for Quadruped Locomotion [pdf] pdf   bibtex
@techreport{winkler13,
  author      = {Winkler, Alexander W.},
  title       = {Path Planning and Adaptive Execution based on Force-Feedback 
                 for Quadruped Locomotion},
  institution = {Karlsruhe Institute of Technology and
                 Italian Institute of Technology},
  year        = {2013},
  note        = {Masters Thesis},
  url_pdf     = {mypdfs/13-msc-thesis-winkler.pdf},
}

Implementation of a Software-Agent to Control a Microgripper in a Dezentralized Manner. Winkler, A. W. Technical Report Karlsruhe Institute of Technology. Bachelors Thesis, 2012.
Implementation of a Software-Agent to Control a Microgripper in a Dezentralized Manner [pdf] pdf   bibtex
@techreport{winkler12,
  author      = {Winkler, Alexander W.},
  title       = {Implementation of a Software-Agent to Control
                 a Microgripper in a Dezentralized Manner},
  institution = {Karlsruhe Institute of Technology},
  year        = {2012},
  note        = {Bachelors Thesis},
}

Software

All code is published on Github.

Light-weight and extensible C++ library for trajectory optimization for legged robots.

Star Download

Eigen-based and light-weight C++ Interface for NLP Solvers (Ipopt, Snopt).

Star Download

Visualization of legged robots, forces, support areas, ZMP, CoM etc. in ROS rviz.

Star Download

Blog

Welcome to my blog! 🙂 So far a bit philosophy, a bit diary, let's see where it goes.

Six months backpacking

and mastering the Bum Gun

2019-3-30  ·  7 min read

I am sitting on the toilet throwing my shit-stained toilet paper in the trash can under the sink whe... read more

Collect memories or things?

Why they're not so different

2018-12-24  ·  4 min read

It's Christmas Eve and I'm waiting for my plane at LAX scrolling through my Instagram feed. An image ... read more

Living like a Buddhist monk

10 days of silent meditation

2018-10-27  ·  10 min read

My ass hurt, my concentration was gone and time seemed to stand still. I squinted open my eyes just e... read more

Why I'm travelling

Exploration vs exploitation

2018-10-09  ·  4 min read

Nowadays, the reasons for travel are assumed to be so obvious, the benefits so universally agreed-u... read more

How to postpone your dreams

Why money can help

2018-09-12  ·  3 min read

Of a 168-hour week, 56 hours are typically spent sleeping and 40 hours earning money. That leaves 72 ... read more