A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots

This paper contributes towards the development and comparison of Divergent-Component-of-Motion (DCM) based control architectures for humanoid robot locomotion. More precisely, we present and compare several DCM based implementations of a three layer control architecture. From top to bottom, these three layers are here called: trajectory optimization, simplified model control, and whole-body QP control. All layers use the DCM concept to generate references for the layer below. For the simplified model control layer, we present and compare both instantaneous and Receding Horizon Control controllers. For the whole-body QP control layer, we present and compare controllers for position and velocity control robots. Experimental results are carried out on the one-meter tall iCub humanoid robot. We show which implementation of the above control architecture allows the robot to achieve a walking velocity of 0.41 meters per second.Comment: Submitted to Humanoids201

Solving Footstep Planning as a Feasibility Problem Using L1-Norm Minimization

Extended version of the paper to be published in IEEE Robotics and Automation LettersInternational audienceOne challenge of legged locomotion on uneven terrains is to deal with both the discrete problem of selecting a contact surface for each footstep and the continuous problem of placing each footstep on the selected surface. Consequently, footstep planning can be addressed with a Mixed Integer Program (MIP), an elegant but computationally-demanding method, which can make it unsuitable for online planning. We reformulate the MIP into a cardinality problem, then approximate it as a computationally efficient l1-norm minimisation, called SL1M. Moreover, we improve the performance and convergence of SL1M by combining it with a sampling-based root trajectory planner to prune irrelevant surface candidates. Our tests on the humanoid Talos in four representative scenarios show that SL1M always converges faster than MIP. For scenarios when the combinatorial complexity is small (< 10 surfaces per step), SL1M converges at least two times faster than MIP with no need for pruning. In more complex cases, SL1M converges up to 100 times faster than MIP with the help of pruning. Moreover, pruning can also improve the MIP computation time. The versatility of the framework is shown with additional tests on the quadruped robot ANYmal

Fuzzy optimisation based symbolic grounding for service robots

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophySymbolic grounding is a bridge between task level planning and actual robot sensing and actuation. Uncertainties raised by unstructured environments make a bottleneck for integrating traditional artificial intelligence with service robotics. In this research, a fuzzy optimisation based symbolic grounding approach is presented. This approach can handle uncertainties and helps service robots to determine the most comfortable base region for grasping objects in a fetch and carry task. Novel techniques are applied to establish fuzzy objective function, to model fuzzy constraints and to perform fuzzy optimisation. The approach does not have the short comings of others’ work and the computation time is dramatically reduced in compare with other methods. The advantages of the proposed fuzzy optimisation based approach are evidenced by experiments that were undertaken in Care-O-bot 3 (COB 3) and Robot Operating System (ROS) platforms

Iterative Path Optimisation for Personalised Dressing Assistance using Vision and Force Information

We propose an online iterative path optimisation method to enable a Baxter humanoid robot to assist human users to dress. The robot searches for the optimal personalised dressing path using vision and force sensor information: vision information is used to recognise the human pose and model the movement space of upper-body joints; force sensor information is used for the robot to detect external force resistance and to locally adjust its motion. We propose a new stochastic path optimisation method based on adaptive moment estimation. We first compare the proposed method with other path optimisation algorithms on synthetic data. Experimental results show that the performance of the method achieves the smallest error with fewer iterations and less computation time. We also evaluate real-world data by enabling the Baxter robot to assist real human users with their dressing

A Model-based Hierarchical Controller for Legged Systems subject to External Disturbances

Xin G, Lin H-C, Smith J, Cebe O, Mistry M. A Model-based Hierarchical Controller for Legged Systems subject to External Disturbances. In: IEEE/RSJ Int. Conf. on Robotics and Automation. 2018.Legged robots have many potential applications in real-world scenarios where the tasks are too dangerous for humans, and compliance is needed to protect the system against external disturbances and impacts. In this paper, we propose a model-based controller for hierarchical tasks of legged systems subject to external disturbance. The control framework is based on projected inverse dynamics controller, such that the control law is decomposed into two orthogonal subspaces, i.e., the constrained and the unconstrained subspaces. The unconstrained component controls multiple desired tasks with impedance responses. The constrained space controller maintains the contact subject to unknown external disturbances, without the use of any force/torque sensing at the contact points. By explicitly modelling the external force, our controller is robust to external disturbances and errors arising from incorrect dynamic model information. The main contributions of this paper include (1) incorporating an impedance controller to control external disturbances and allow impedance shaping to adjust the behaviour of the motion under external disturbances, (2) optimising contact forces within the constrained subspace that also takes into account the external disturbances without using force/torque sensors at the contact locations. The techniques are evaluated on the ANYmal quadruped platform under a variety of scenarios