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Concurrent Optimization of Mechanical Design and Locomotion Control of a Legged Robot

  • Authors: Digumarti, K. M.; Gehring, C.; Coros, S.; Hwangbo, J.; Siegwart, R.

This paper introduces a method to simultaneously optimize design and control parameters for legged robots to improve the performance of locomotion based tasks. The morphology of a quadrupedal robot was optimized for a trotting and bounding gait to achieve a certain speed while tuning the control parameters of a robust locomotion controller at the same time. The results of the optimization show that a change of the structure of the robot can help increase its admissable top speed while using the same actuation units.

Posted on: July 16, 2014

On the Comparison of Gauge Freedom Handling in Optimization-Based Visual-Inertial State Estimation

  • Authors: Zhang, Zichao; Gallego, Guillermo; Scaramuzza, Davide

  It is well known that visual-inertial state estimation is possible up to a four degrees-of-freedom (DoF) transformation (rotation around gravity and translation), and the extra DoFs (“gauge freedom”) have to be handled properly. While different approaches for handling the gauge freedom have been used in practice, no previous study has been carried out to …

Posted on: June 12, 2018

Voxgraph: Globally Consistent, Volumetric Mapping using Signed Distance Function Submaps

Authors: Victor Reijgwart*, Alexander Millane*, Helen Oleynikova, Roland Siegwart, Cesar Cadena, Juan Nieto



Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and global consistency, most require more computational resources than may be available on-board small robots. We propose a framework that creates globally consistent volumetric maps on a CPU and is lightweight enough to run on computationally constrained platforms.
Our approach represents the environment as a collection of overlapping Signed Distance Function (SDF) submaps, and maintains global consistency by computing an optimal alignment of the submap collection. By exploiting the underlying SDF representation, we generate correspondence-free constraints between submap pairs that are computationally efficient enough to optimize the global problem each time a new submap is added. We deploy the proposed system on a hexacopter MAV with an Intel i7-8650U CPU in two realistic scenarios: mapping a large-scale area using a 3D LiDAR, and mapping an industrial space using an RGB-D camera. In the large-scale outdoor experiments, the system optimizes a 120x80m map in less than 4s and produces absolute trajectory RMSE of less than 1m over 400m trajectories. Our complete system, called voxgraph, is available as open source (https://github.com/ethz-asl/voxgraph).


  • Published in: IEEE Robotics and Automation Letters (Volume: 5, Issue: 1, Jan. 2020)
  • DOI: 10.1109/LRA.2019.2953859
  • Read paper
  • Date: 2019
Posted on: November 27, 2020