We present a motion planning and control framework for ALMA, a torque-controlled quadrupedal robot equipped with a six degrees of freedom robotic arm capable of performing dynamic locomotion while executing manipulation tasks. The online motion planning framework, together with a whole-body controller based on a hierarchical optimization algorithm, enable the system to walk, trot and pace while executing tasks such as fixed-position end-effector control, reactive human-robot collaboration and torso posture optimization to increase the arm's kinematic reachability. The torque controllability of the whole system enables the implementation of compliant behavior, allowing a user to safely interact with the robot in a very natural way. We verify our framework on the real robot by performing tasks such as opening a door and carrying a payload together with a human.
Exoskeletons are a promising technology that enables individuals with mobility limitations to walk again.As the 2016 Cybathlon illustrated, however, the community has a considerable way to go before exoskeletons have the necessary capabilities to be incorporated into daily life. While most exoskeletons power only hip and knee flexion, Team Institute for Human and Machine Cognition (IHMC) presents a new exoskeleton, Mina v2, which includes a powered ankle dorsi/plantar flexion (Figure 1). As our entry to the 2016 Cybathlon Powered Exoskeleton Competition, Mina v2' s performance allowed us to explore the effectiveness of its powered ankle compared to other powered exoskeletons for pilots with paraplegia. We designed our gaits to incorporate powered ankle plantar flexion to help improve mobility, which allowed our pilot to navigate the given Cybathlon tasks quickly, including those that required ascending movements, and reliably achieve average, conservative walking speeds of 1.04 km/h (0.29 m/s). This enabled our team to place second overall in the Powered Exoskeleton Competition in the 2016 Cybathlon.
We present a fully-integrated sensing and control system which enables mobile manipulator robots to execute building tasks with millimeter-scale accuracy on building construction sites. The approach leverages multi-modal sensing capabilities for state estimation, tight integration with digital building models, and integrated trajectory planning and whole-body motion control. A novel method for high-accuracy localization updates relative to the known building structure is proposed. The approach is implemented on a real platform and tested under realistic construction conditions. We show that the system can achieve sub-cm end-effector positioning accuracy during fully autonomous operation using solely onboard sensing. contributed to the state estimation and high accuracy localization {blumh, gawela, rsiegwart}@ethz.ch. Timothy Sandy contributed to the state estimator, and motion control tsandy@ethz.ch. Koen Krämer, Johannes Pankert, Farbod Farshidian, Marco Hutter contributed to the Motion planning and control {kokraeme, pankertj, farshidian, mahutter}@ethz.ch. Selen Ercan, Fabio Gramazio contributed to the building task interface {ercan, gramazio}@arch.ethz.ch.
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