• Corpus ID: 219176847

Time Variable Minimum Torque Trajectory Optimization for Autonomous Excavator

  title={Time Variable Minimum Torque Trajectory Optimization for Autonomous Excavator},
  author={Yajue Yang and Jia Pan and Pinxin Long and Xibin Song and Liangjun Zhang},
In this paper, we present a minimal torque and time variable trajectory optimization method for autonomous excavator considering the soil-tool interaction. The method formulates the excavation motion generation as a trajectory optimization problem and takes into account geometric, kinematic and dynamics constraints. To generate time-efficient trajectory and improve the overall optimization efficiency, we propose a time variable trajectory optimization mechanism so that the time intervals… 

Real-Time Motion Planning of a Hydraulic Excavator using Trajectory Optimization and Model Predictive Control

This work presents the first real-time motion planning framework that satisfies constraints of a hydraulic excavator, such as force/torque, power, cylinder displacement, and flow rate limits.

Variable-time-interval trajectory optimization-based dynamic walking control of bipedal robot

Abstract Bipedal robots by their nature show both hybrid and underactuated system features which are not stable and controllable at every point of joint space. They are only controllable on certain

Dynamic Modeling of Bucket-Soil Interactions Using Koopman-DFL Lifting Linearization for Model Predictive Contouring Control of Autonomous Excavators

A lifting-linearization method based on the Koopman operator and Dual Faceted Linearization is applied to the control of a robotic excavator, where a cost functional is minimized as a convex optimization problem thanks to the linear dynamics in the lifted space.

Learning of Causal Observable Functions for Koopman-DFL Lifting Linearization of Nonlinear Controlled Systems and Its Application to Excavation Automation

This work presents a method for eliminating such anti-causal components of the observables and lifting the system using only causal observables, and is applied to excavation automation, a complex nonlinear dynamical system, to obtain a low-order lifted linear model for control design.



Planning and Control for Autonomous Excavation

A novel planning and control approach for autonomous excavation that is independent of the soil composition and goes beyond a single dig is presented, and a large-scale iterative planner is proposed to consecutively execute single digs until a desired ground geometry is achieved.

Dynamically optimal trajectories for earthmoving excavators

Compact Reachability Map for Excavator Motion Planning

It is shown the pre-computed reachability map can be used to develop new excavator motion planning approach and efficiently compute the feasible full-bucket trajectory for single step excavation operation.

Synthesis of tactical plans for robotic excavation

This thesis describes an approach to synthesizing plans for robotic excavators. Excavation tasks range from loading a pile of soil to cutting a geometrically described volume of earth--for a trench

Motion planning with sequential convex optimization and convex collision checking

A sequential convex optimization procedure, which penalizes collisions with a hinge loss and increases the penalty coefficients in an outer loop as necessary, and an efficient formulation of the no-collisions constraint that directly considers continuous-time safety are presented.

Randomized kinodynamic planning

  • S. LaValleJ. Kuffner
  • Mathematics
    Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)
  • 1999
A state-space perspective on the kinodynamic planning problem is presented, and a randomized path planning technique that computes collision-free kinodynamic trajectories for high degree-of-freedom problems is introduced.

Newton-type algorithms for dynamics-based robot movement optimization

It is shown through several case studies that, with exact gradient and Hessian information, descent-based optimization methods can be forged into an effective and reliable tool for generating physically natural robot movements.

Task Planning For Robotic Excavation

  • Sanjiv SinghR. Simmons
  • Computer Science
    Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems
  • 1992
A methodology to automatically generate plans for a robot excavator like a bucket loader or a backhoe as one of constrained optimization in an actkm space that is spanned by the parameters of a prototypical digging plan is proposed.

Asymptotically optimal sampling-based kinodynamic planning

Two new methods, STABLE_SPARSE_RRT (SST) and SST*, result from this analysis, which are asymptotically near-optimal and optimal, respectively, and are shown to converge fast to high-quality paths, while they maintain only a sparse set of samples, which makes them computationally efficient.