Massimo Vespignani

Towards dynamic trot gait locomotion: Design, control, and experiments with Cheetah-cub, a compliant quadruped robot

We present the design of a novel compliant quadruped robot, called Cheetah-cub, and a series of locomotion experiments with fast trotting gaits. The robot’s leg configuration is based on a spring-loaded, pantograph mechanism with multiple segments. A dedicated open-loop locomotion controller was derived and implemented. Experiments were run in simulation and in hardware on flat terrain and with a step down, demonstrating the robot’s self-stabilizing properties. The robot reached a running trot with short flight phases with a maximum Froude number of FR = 1.30, or 6.9 body lengths per second. Morphological parameters such as the leg design also played a role. By adding distal in-series elasticity, self-stability and maximum robot speed improved. Our robot has several advantages, especially when compared with larger and stiffer quadruped robot designs. (1) It is, to the best of the authors’ knowledge, the fastest of all quadruped robots below 30kg (in terms of Froude number and body lengths per second). (2) It shows self-stabilizing behavior over a large range of speeds with open-loop control. (3) It is lightweight, compact, and electrically powered. (4) It is cheap, easy to reproduce, robust, and safe to handle. This makes it an excellent tool for research of multi-segment legs in quadruped robots.

Roombots: A Hardware Perspective on 3D Self-Reconfiguration and Locomotion with a Homogeneous Modular Robot

In this work we provide hands-on experience on designing and testing a self-reconfiguring modular robotic system, Roombots (RB), to be used among others for adaptive furniture. In the long term, we envision that RB can be used to create sets of furniture, like stools, chairs and tables that can move in their environment and that change shape and functionality during the day. In this article, we present the first results towards that long term vision. We demonstrate locomotion and reconfiguration of single and metamodule RB over 3D surfaces, in a structured environment equipped with embedded connection ports. RB assemblies can move around in non-structured environments, by using rotational or wheel-like locomotion. We show a proof of concept for transferring a Roombots metamodule back into the structured grid, by aligning it in an entrapment mechanism. Finally, we analyze remaining challenges to master the full Roombots scenario, and discuss the impact on future Roombots hardware.

A mechatronic platform for behavioral analysis on nonhuman primates

In this work we present a new mechatronic platform for measuring behavior of nonhuman primates, allowing high reprogrammability and providing several possibilities of interactions. The platform is the result of a multidisciplinary design process, which has involved bio-engineers, developmental neuroscientists, primatologists, and roboticians to identify its main requirements and specifications. Although such a platform has been designed for the behavioral analysis of capuchin monkeys (Cebus apella), it can be used for behavioral studies on other nonhuman primates and children. First, a state-of-the-art principal approach used in nonhuman primate behavioral studies is reported. Second, the main advantages of the mechatronic approach are presented. In this section, the platform is described in all its parts and the possibility to use it for studies on learning mechanism based on intrinsic motivation discussed. Third, a pilot study on capuchin monkeys is provided and preliminary data are presented and discussed.

Gait optimization for roombots modular robots — Matching simulation and reality

The design of efficient locomotion gaits for robots with many degrees of freedom is challenging and time consuming even if optimization techniques are applied. Control parameters can be found through optimization in two ways: (i) through online optimization where the performance of a robot is measured while trying different control parameters on the actual hardware and (ii) through offline optimization by simulating the robots behavior with the help of models of the robot and its environment. In this paper, we present a hybrid optimization method that combines the best properties of online and offline optimization to efficiently find locomotion gaits for arbitrary structures. In comparison to pure online optimization, both the number of experiments using robotic hardware as well as the total time required for finding efficient locomotion gaits get highly reduced by running the major part of the optimization process in simulation using a cluster of processors. The presented example shows that even for robots with a low number of degrees of freedom the time required for optimization can be reduced by a factor of 2.5 to 30, at least, depending on how extensive the search for optimized control parameters should be. Time for hardware experiments becomes minimal. More importantly, gaits that can possibly damage the robotic hardware can be filtered before being tried in hardware. Yet in contrast to pure offline optimization, we reach well matched behavior that allows a direct transfer of locomotion gaits from simulation to hardware. This is because through a meta-optimization we adapt not only the locomotion parameters but also the parameters for simulation models of the robot and environment allowing for a good matching of the robot behavior in simulation and hardware. We validate the proposed hybrid optimization method on a structure composed of two Roombots modules with a total number of six degrees of freedom. Roombots are self-reconfigurable modular robots that can form arbitrary structures with many degrees of freedom through an integrated active connection mechanism.

Role of compliance on the locomotion of a reconfigurable modular snake robot

This paper presents the results of a study on the effect of in-series compliance on the locomotion of a simulated 8-DoF Lola-OP™ Modular Snake Robot with added compliant elements. We explore whether there is an optimal stiffness for gait, terrain type, or several gaits and several terrains (i.e. a good “general-purpose” stiffness). Compliance was simulated using ball joints with eight different levels of stiffness. Two snake locomotion gaits (rolling and sidewinding) were tested over flat ground and three different types of rough terrains. We performed grid search and Particle Swarm Optimization to identify the locomotion parameters leading to fast locomotion and analyzed the best candidates in terms of locomotion speed and energy efficiency (cost of transport). Contrary to our expectations, we did not observe a clear trend that would favor the use of compliant elements over rigid structures. For sidewinding, compliant and stiff elements lead to comparable performances. For rolling gait, the general rule seems to be “the stiffer, the better”.

An experimental study on the role of compliant elements on the locomotion of the self-reconfigurable modular robots Roombots

This paper presents the results of a study on the exploitation of compliance in structures made of self-reconfigurable modular robots - Roombots. This research was driven by the following three hypotheses: (1) compliance can improve locomotion performance; (2) different types of compliance will result in diverse locomotion behaviors; (3) control parameters optimized for a medium level of compliance will perform better for other values of compliance than parameters optimized for extremal compliance. Two types of in-series compliant elements were tested, with five different stiffness values for each of them, on a structure made of two Roombots modules. We ran dedicated on-line locomotion parameter optimizations for six different configurations and evaluated their performance for different stiffness values. Hypothesis 1 was confirmed for both types of compliant elements, with a peak of performance for an optimal level of compliance. The variety of locomotion strategies obtained for the different structures confirms hypothesis 2. Hypothesis 3 was only partially confirmed.

Automatic Generation of Reduced CPG Control Networks for Locomotion of Arbitrary Modular Robot Structures

The design of efficient locomotion controllers for arbitrary structures of reconfigurable modular robots is challenging because the morphology of the structure can change dynamically during the completion of a task. In this paper, we propose a new method to automatically generate reduced Central Pattern Generator (CPG) networks for locomotion control based on the detection of bio-inspired sub-structures, like body and limbs, and articulation joints inside the robotic structure. We demonstrate how that information, coupled with the potential symmetries in the structure, can be used to speed up the optimization of the gaits and investigate its impact on the solution quality (i.e. the velocity of the robotic structure and the potential internal collisions between robotic modules). We tested our approach on three simulated structures and observed that the reduced network topologies in the first iterations of the optimization process performed significantly better than the fully open ones.

Rich periodic motor skills on humanoid robots: Riding the pedal racer

Just as their discrete counterparts, periodic or rhythmic dynamic motion primitives allow easily modulated and robust motion generation, but for periodic tasks. In this paper we present an approach for modulating periodic dynamic movement primitives based on force feedback, allowing for rich motor behavior and skills. We propose and evaluate the combination of feedback and learned feed-forward terms to fully adapt the motions of a robot in order to achieve a desired force interaction with the environment. For the learning we employ the notion of repetitive control, which can effectively minimize the error of behavior towards a given reference. To demonstrate the approach, we show results of simulated and real world experiments on a compliant humanoid robot COMAN. We show the initial results of utilizing the approach to control a pedal-racer, a demanding balance toy best described as a hybrid between a skateboard and a bicycle.

Collaborative manipulation and transport of passive pieces using the self-reconfigurable modular robots roombots

Manipulation and transport of objects using mobile robotic platforms is a well studied field with several successful approaches. The main difficulty while using such platforms is the lack of adaptation capabilities to changes in the environment and the restriction to flat working areas. In this paper, we present a novel manipulation and transport framework using the self-reconfigurable modular robots Roombots to collaboratively carry arbitrarily shaped passive elements in a non-regular 3D environment equipped with passive connectors. A hierarchical planner based on the notion of virtual kinematic chain is used to generate collision-free and hardware-friendly paths as well as sequences of collaborative manipulations. To the best of our knowledge, this is the first example of manipulation of fully passive elements in an arbitrary 3D environment using mobile self-reconfigurable robots. The simulated results show that the planner is robust to arbitrary complex environments with randomly distributed connectors. In addition to simulation results, a proof of concept of the manipulation of one passive element with two real Roombots meta-modules is described.

Dynamic Characterization and Interaction Control of the CBM-Motus Robot for Upper-Limb Rehabilitation

This paper presents dynamic characterization and control of an upper-limb rehabilitation machine aimed at improving robot performance in the interaction with the patient. An integrated approach between mechanics and control is the key issue of the paper for the development of a robotic machine with desirable dynamic properties. Robot inertial and acceleration properties are studied in the workspace via a graphical representation based on ellipses. Robot friction is experimentally retrieved by means of a parametric identification procedure. A current-based impedance control is developed in order to compensate for friction and enhance control performance in the interaction with the patient by means of force feedback, without increasing system inertia. To this end, servo-amplifier motor currents are monitored to provide force feedback in the interaction, thus avoiding the need for force sensors mounted at the robot end-effector. Current-based impedance control is implemented on the robot; experimental results in free space as well as in constrained space are provided.