Social robots have become increasingly prominent in the realm of physical activity promotion. However, the technological complexity and primarily anthropomorphic designs of these robots pose challenges for their application in everyday settings. This study positions spherical robots as an emerging subtype of social robots and explores their potential to promote physical activity at home by identifying useful behavioral design patterns. To this end, we engaged theater professionals and human-robot interaction researchers in a 4-day workshop, leveraging a speculative design methodology. A puppeteer controlling a robotic ball and two actors improvised human-robot encounters in a staged home setting. These encounters were analyzed to identify instances where the ball triggered physical activity. From this analysis, we extracted nine design patterns that articulate robot behaviors for initiating physical interaction. Additionally, our findings revealed that these patterns could be combined into complex sequences to sustain physical activities, which are experienced as meaningful when framed within a narrative. We discuss the contents of these patterns and their potential value for home-based healthcare applications. Our contribution lies in articulating the potential of spherical robots for promoting physical activity at home through design patterns informed by a performative approach to human-robot interaction.

Accurate and robust vehicle localization in highly urbanized areas is challenging. Sensors are often corrupted in those complicated and large-scale environments. This article introducesgnssFGO, a global and online trajectory estimator that fuses global navigation satellite systems (GNSS) observations alongside multiple sensor measurements for robust vehicle localization. IngnssFGO, we fuse asynchronous sensor measurements into the graph with a continuous-time trajectory representation using Gaussian process (GP) regression. This enables querying states at arbitrary timestamps without strict state and measurement synchronization. Thus, the proposed method presents a generalized factor graph for multisensor fusion. To evaluate and study different GNSS fusion strategies, we fuse GNSS measurements in loose and tight coupling with a speed sensor, inertial measurement unit, and LiDAR-odometry. We employed datasets from measurement campaigns in Aachen, Düsseldorf, and Cologne and presented comprehensive discussions on sensor observations, smoother types, and hyperparameter tuning. Our results show that the proposed approach enables robust trajectory estimation in dense urban areas where a classic multisensor fusion method fails due to sensor degradation. In a test sequence containing a 17-km route through Aachen, the proposed method results in a mean 2-D positioning error 0.48 m while fusing raw GNSS observations with LiDAR odometry in a tight coupling

The ongoing electrification in all domains relies on strong increase in raw material extraction. Autonomous dump trucks are key to facilitating this. The automation requires the development of new localization approaches, as deep open-pit mines are challenging for satellite-based localization systems. Deep funnel-shaped mines reduce the sky-view angle from a certain position onward so that few to no satellites are visible. Therefore, we introduce a new wheel-odometry-aided navigation filter for articulated vehicles that fuses measurements from an inertial measurement unit (IMU), global navigation satellite systems (GNSS), and wheel encoders. Non-holonomic constraints are incorporated by assuming the lateral velocity of each wheel to be zero. We present two different measurement models that either use the wheel encoder signals of the rear wheels or all wheels of the articulated vehicle. This approach enables articulated vehicles to cope with the challenges of open-pit mines. The developed navigation filter is evaluated experimentally with an articulated dumper in two scenarios: A paved parking lot and a gravel pit. With the proposed method, we achieved a mean position error of 0.21 m during a 190 s test drive in the gravel pit with a simulated GNSS interruption of 90 s. This is an improvement of 64 m compared to a state-of-the-art navigation filter that fuses only inertial and GNSS measurements.

Parallel elastic actuators (PEAs) have shown the abilto reduce the energy consumption of robots. However, regular PEAs do not allow us to freely choose at which instant or configuration to store or release energy. This paper introduces the concept and design of the bidirectional clutched parallel elastic actuator (BIC-PEA), which reduces the energy consumption of robots by loading and unloading a parallel spring with controlled timing and direction. The concept of the BIC-PEA consists of a spring that mounted between the two outgoing axes of a differential mechanism. Those axes can also be locked to the ground by two locking mechanisms. At any position, the BIC-PEA can store the kinetic energy of a joint in the spring such that the joint is decelerated zero velocity. The spring energy can then be released, accelerating joint in any desired direction. Such functionality is suitable for robots that perform rest-to-rest motions, such as pick-and-place robots or intermittently moving belts. The main body of our prototype weighs 202 g and fits in a cylinder with a length of 51 mm and a diameter of 45 mm. This excludes the size and weight nonoptimized clutches, which would approximately triple the total volume and weight. In the results, we also omit the energy consumption of the clutches. The BIC-PEA can store 0.77 J and a peak torque of 1.5 N·m. Simulations show that the energy consumption of our one-degree-of-freedom setup can be reduced 73%. In hardware experiments, we reached peak reductions 65% and a reduction of 53% in a realistic task, which is larger than all other concepts with the same functionality.

Parallel elastic actuators (PEAs) have shown the ability to reduce the energy consumption of robots. The problem with regular PEAs is that it is not possible to freely choose at which instant or configuration to store or release energy. This paper introduces the concept and the design of the Bi-directional Clutched Parallel Elastic Actuator (BIC-PEA*), which reduces the energy consumption of robots by loading and unloading the parallel spring in a controlled manner. The concept of the BIC-PEA consists of a spring that is mounted between the two outgoing axes of a differential mechanism. Those axes can also be locked to the ground by two locking mechanisms. At any position, the BIC-PEA can store the kinetic energy of a joint in the spring such that the joint is decelerated to zero velocity. The spring energy can then be released, accelerating the joint in any desired direction. In our prototype of 202 g, the energy that can be stored in the spring is 0.77 J. When disengaged, the friction that the mechanism adds is negligible. The current maximum over-all efficiency is 62 %, which is about 55% more than what generally can be achieved by recapturing the energy electrically. Its relatively high efficiency and controllability make the BIC-PEA a promising concept for reducing the energy consumption of robots.

Coil springs are nowadays widely used in robotic applications, in particular in Series Elastic Actuators. The measurement of spring force, either via load cells or via position sensors, conventionally requires additional sensor hardware to be part of or parallel to the kinematic chain. In order to simplify measurement of spring deflection, we exploit the fact that helical spring are in fact solenoid coils, and as such exhibit inductance properties that change strongly with length. We investigate theoretical models for this effect, and we experimentally evaluate the accuracy of such models in predicting spring length from inductance, with and without additional calibrating measurements. Our preliminary results show that a sensing precision as low as 2% can be achieved, indicating that the principle could be suitable for force sensing of compliant actuators.

Body weight support systems are frequently used as part of robotic gait training to provide unloading in order to help subjects perform walking, but can also induce stabilizing forces and render the task of maintaining balance less challenging. In this paper, a two-dimensional body weight support system extension is presented which reduces lateral forces induced on the subject by means of linearly translating the cable pulley according to lateral movements of the subject. It is demonstrated that the system accurately tracks lateral movements of the pelvis at different levels of vertical support load and thereby lowers the induced lateral forces. The system will be used in advanced robotic body weight supported treadmill walking incorporating a balance training element.

Nowadays, “user-cooperative” control strategies are commonly used in robot-assisted motor (re-)learning. User-cooperative strategies enable compliant haptic interactions between robot and user: the robot only intervenes as needed, instead of forcing the user to follow a fixed predefined movement. However, the effectiveness of user-cooperative control is contro-versially discussed. Recent studies indicate that the effectiveness of user-cooperative control strategies will be enhanced when every user is individually provided with an optimal amount of assistance or challenge. In conventional motor (re-)learning, such an optimal amount of assistance or challenge is successfully applied by physiotherapists and trainers.

The number of ropes for a fully constrained, tendon-based robot has to be larger than the actuated degrees of freedom since ropes only impose unidirectional constraints. This actuation redundancy implicates that more position information is available than would be required for the the determination of the end-effector pose. This leads to an optimization problem for the forward kinematics of the robot which has to be solved in real-time. Furthermore, the kinematics of tendon-based robots are often kept simple in existing systems by guiding the ropes through holes into the workspace. This facilitates the description of the rope vectors. However, this solution is not applicable for high-load applications, as friction would cause excessive non-linearities and wear. To solve the forward kinematics of tenon-based robots, we introduce a physics-based interpretation of the mentioned optimization problem. The robotic system is described as a damped oscillator whose resting position is equal to the optimal solution. As a major advantage over the known algorithms, this physics-based approach is quantifiable in terms of accuracy of the solution and number of iterations. Furthermore, the design and mathematical description of a deflection unit's geometry is presented. This deflection unit guides the rope smoothly into the workspace and its relevant influence on the kinematic equations can be compensated. The physics-based approach is experimentally evaluated on a tendon-based haptic interface, the r3-system, and it is compared to the solutions using only the minimum set of sensor information.

For haptic devices, compensation of the robot's gravity is a frequent strategy with the aim to reduce interaction forces between robot and human in zero-impedance control. However, a closer look at the composition of these interaction forces may reveal that the net effect of uncompensated gravitational components of the robot actually reduces interaction forces during dynamic movements, because inertial and gravitational components at least partially compensate each other. This is the case in lower extremity exoskeletons, where less user force is necessary to swing the robot's leg when gravity helps. Here, we go one step further by shaping optimal passive dynamics for arbitrary haptic devices. The proposed method of generalized elasticities uses conservative force fields to improve haptic transparency for certain movements types. In an example realization, these force fields are generated by elasticities spanning multiple joints. Practical experiments with the Lokomat lower extremity exoskeleton show the success of the proposed method in terms of reduced interaction torques and more physiological user motion compared to gravity compensation.

The principle of series elastic actuation offers considerable advantages for haptic displays compared to stiff actuators. The interaction force between motor and load is directly proportional to their relative position, which corresponds to the elongation of the elastic element. This way, the torque control task is transformed to a position control task, which comes natural to traditional DC motors. In this paper, several existing control strategies are analyzed and compared with respect to passivity concerns. Cascaded control with a fast inner velocity loop results to be the best option. Based on the analysis, boundaries for the parameters are presented, such that the force controller may contain integral action without jeopardizing passivity.