300 research outputs found
Mobility Strategy of Multi-Limbed Climbing Robots for Asteroid Exploration
Mobility on asteroids by multi-limbed climbing robots is expected to achieve
our exploration goals in such challenging environments. We propose a mobility
strategy to improve the locomotion safety of climbing robots in such harsh
environments that picture extremely low gravity and highly uneven terrain. Our
method plans the gait by decoupling the base and limbs' movements and adjusting
the main body pose to avoid ground collisions. The proposed approach includes a
motion planning that reduces the reactions generated by the robot's movement by
optimizing the swinging trajectory and distributing the momentum. Lower motion
reactions decrease the pulling forces on the grippers, avoiding the slippage
and flotation of the robot. Dynamic simulations and experiments demonstrate
that the proposed method could improve the robot's mobility on the surface of
asteroids.Comment: Submitted version of paper accepted for presentation at the CLAWAR
2023 (26th International Conference on Climbing and Walking Robots and the
Support Technologies for Mobile Machines
Motion Planning for a Climbing Robot with Stochastic Grasps
Motion planning for a multi-limbed climbing robot must consider the robot's
posture, joint torques, and how it uses contact forces to interact with its
environment. This paper focuses on motion planning for a robot that uses
nontraditional locomotion to explore unpredictable environments such as martian
caves. Our robotic concept, ReachBot, uses extendable and retractable booms as
limbs to achieve a large reachable workspace while climbing. Each extendable
boom is capped by a microspine gripper designed for grasping rocky surfaces.
ReachBot leverages its large workspace to navigate around obstacles, over
crevasses, and through challenging terrain. Our planning approach must be
versatile to accommodate variable terrain features and robust to mitigate risks
from the stochastic nature of grasping with spines. In this paper, we introduce
a graph traversal algorithm to select a discrete sequence of grasps based on
available terrain features suitable for grasping. This discrete plan is
complemented by a decoupled motion planner that considers the alternating
phases of body movement and end-effector movement, using a combination of
sampling-based planning and sequential convex programming to optimize
individual phases. We use our motion planner to plan a trajectory across a
simulated 2D cave environment with at least 95% probability of success and
demonstrate improved robustness over a baseline trajectory. Finally, we verify
our motion planning algorithm through experimentation on a 2D planar prototype.Comment: 7 pages, 7 figure
Mobility of bodies in contact. II. How forces are generated bycurvature effects
For part I, see ibid., p.696-708. The paper considers how forces are produced by compliance and surface curvature effects in systems where an object a is kinematically immobilized to second-order by finger bodies Al,...,Ak. A class of configuration-space based elastic deformation models is introduced. Using these elastic deformation models, it is shown that any object which is kinematically immobilized to first or second-order is also dynamically locally asymptotically stable with respect to perturbations. Moreover, it is shown that for preloaded grasps kinematic immobility implies that the stiffness matrix of the grasp is positive definite. The stability result provides physical justification for using second-order effects for purposes of immobilization in practical applications. Simulations illustrate the concepts
Optimization Based Motion Planning for Multi-Limbed Vertical Climbing Robots
Motion planning trajectories for a multi-limbed robot to climb up walls
requires a unique combination of constraints on torque, contact force, and
posture. This paper focuses on motion planning for one particular setup wherein
a six-legged robot braces itself between two vertical walls and climbs
vertically with end effectors that only use friction. Instead of motion
planning with a single nonlinear programming (NLP) solver, we decoupled the
problem into two parts with distinct physical meaning: torso postures and
contact forces. The first part can be formulated as either a mixed-integer
convex programming (MICP) or NLP problem, while the second part is formulated
as a series of standard convex optimization problems. Variants of the two wall
climbing problem e.g., obstacle avoidance, uneven surfaces, and angled walls,
help verify the proposed method in simulation and experimentation.Comment: IROS 2019 Accepte
A Novel Energy-Efficient Hexapod Robot Design using a Rotary Encoder-Embedded Weight-Bearing Wheel
The direct proportionality that exists between the joint actuator rated torque of conventional hexapod robots and the payload mass makes them unsuitable for applications that require energy efficiency. In this paper, we propose a novel hexapod robot design which involves the incorporation of a rotary encoder-embedded weight-bearing wheel to relax the stringent limitations on the choice of the robot’s joint actuator torques and the battery capacity. The results of the prototype implementation showed that our design inherits the merits of easy linear distance measurement via the embedded rotary encoder, low actuator torque and high payload capability from wheeled robots. Keywords: Hexapod robots; Joint actuator; Wheeled robots; Weight-bearing wheel; Rotary encoder; Actuator torque DOI: 10.7176/CTI/8-0
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